Episode 64 - Pamela Harris and Aris Winger

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast. We need a better tagline, but I'm not going to come up with one today. I'm Kevin Knudson, professor of mathematics at the University of Florida. Here is your other host.

Evelyn Lamb: Hi, I’m Evelyn Lamb, a freelance math and science writer in Salt Lake City. And I think that our guests might be able to help us with that tagline. But we'll get to that in a moment because I have to share with you a big kitchen win I had recently.

KK: Okay.

EL: Which is that that I successfully worked with phyllo dough! It was really exciting. I made these little pie pocket things with a potato and olive filling. It was so good. And the phyllo dough didn't make me want to tear out my hair. It was just like, best day ever.

KK: Did you make it from scratch?

EL: No, I mean, I bought frozen phyllo dough.

KK: Okay, all right.

EL: Yeah, yeah, I’m not at that level.

KK: I’ve never worked with that stuff. Although my son and I made made gyoza last month, which, again, you know, that that's a lot of work to because you start folding up these dumplings, and you know. They’re fantastic. It's much better. So, yeah, enough. Now I'm getting hungry. Okay. It's mid afternoon. It's not time for supper yet. So today we have we have a twofer today. This is this is going to be great, great fun. It's like a battle royale going here. This will be so much fun. So today we are joined by Pamela Harris and Aris winger. And why don't you guys introduce yourself? Let's start with Pamela.

Pamela Harris: Hi, everyone. I like how we're on Zoom, and so I get to wave. But that’s really only to the people on the call. So for those listening, imagine that I waved at you. So I am super excited to be here with you all today. I'm an associate professor of mathematics at Williams College. And I have gotten the pleasure to work with Dr. Aris Winger on a variety of projects, but I'll let him introduce himself too.

Aris Winger: Hey everybody, I’m Aris Winger. I'm assistant professor at Georgia Gwinnett College. I've been here for a few years now. Yeah, no, we, Pamela and I have been all over the place together. I've been the honored one, to just be her sidekick on a lot of things.

PH: Ha, ha, stop that!

EL: So we're very excited to have you here. So you've worked on several things together. The reason that I thought it would be great to have you on is that one of the things is a podcast called Mathematically Uncensored. And it's a really nice podcast. And I think it has a fantastic tagline. I was telling Aris earlier that it just made me very jealous. So we've we've never quite gotten, like, this snappy tagline. So tell us what your podcast tagline is. And a little bit about the podcast.

PH: Maybe I can do the tagline. So our tagline is “Where our talk is real and complex, but never discrete.”

AW: Yeah, that's right. That is the tagline. And yeah, it's a good one. And sometimes I have to come back to it time and again to remember, so that we live up to that during the podcast. We're taping the podcast later today, actually. And so it should be out on Wednesday. So yeah, the show is about really creating a space for people of color in the mathematical sciences and in mathematics in general, I think. And so one of the ways—I think for us the only way that can happen—is we have to start having hard conversations. Right. And so a realization that comfort and staying on the surface level of our discussions doesn't allow for us to have the true visibility that all people in mathematics should have. And so for too long, we've been talking surface-level and saying, “Oh, we have diversity issues. Oh, we should work harder on inclusion.” No, actually, people are suffering. No, actually, here's our opinion. And stop talking about us; start talking to us. So it really is a space where we're just like, you know what, screw it. Let us say what we think needs to be said. Listen to us. Listen to people who look like us. And yeah it’s hard. It's hard to do the podcast sometimes because when you go deeper and start to talk about harder topics, then there are risks that come with that. Pamela and I, week after week, say, “Oh, I don't know if I really should have said that.” But ,you know, it's what needs to be said, because we're not doing it just for us. We're doing it to model what what needs to happen from everybody in this discipline, to really say the things that need to be said.

KK: Have you gotten negative feedback? I hope not.

AW: Yeah, that’s a good question. So I mean, I think that the emails we've gotten are have been great and supportive. But I think, so for me, I'm expecting no one to say — I’m expecting the usual game as it is, right, that people aren't going to say anything, but of course there's going to be backlash when you start saying things that go against white privilege and go against the current power structures. You know, I'm expecting to be fired this year.

PH: Yeah, those are the conversations that we have constantly — that we’re having on the podcast are things that Aris and I are having conversations about privately. And so part of what's been really eye-opening for me in terms of doing a podcast is that I forget people are listening. There are times Aris and I are having just a conversation, and I forget we're recording. And I say things that I normally would censor. If I were in a mixed crowd, if I were in a department meeting, if I were at a committee meeting for, you know, X organization. And I think it's not so much that we would receive an email that says, “Hey, you shouldn't have said X, Y, and Z,” it’s that we are actually getting targeted. For example, I was just virtually visiting Purdue University giving a talk about a book that Aris and I wrote, supporting students of color. And accidentally, the link got shared to the wrong people. And all of a sudden, I'm getting Zoom-bombed at a conversation. That's targeted, right? So those are the kinds of things that we are experiencing as people of color, and we have to have conversations about how are we ensuring that this isn't the experience when you bring a Black or brown mathematician to talk virtually at your colloquium. And if we're not talking about that, then no one is talking about that, because people are trying to hide their dirty laundry. Purdue University is not putting out an email to their alumni saying, “By the way, we invited Pamela Harris to show up and talk about how we best support students of color. And then we got Zoom-bombed, and somebody was writing the N-word and saying f BLM.” Right? Like, that's not happening.

AW: Yes. Wait, they didn't say anything about it?

PH: Well, they're actively doing things about it. But you know they're not putting out the message.

AW: Right. So then it gets sanitized, right? So a traumatic attack gets sanitized to be something else. There are two things about the podcast that Pamela and I, and the Center for Minorities in the Mathematical Sciences, really are trying to work with is making sure that we call out these things, but then not to center it, right, because the the podcast itself is supposed to be about our experiences. But a lot of ways there's a significant part of our experiences that is tied to having to continuously fight against this type of oppression against us.

EL: Yeah. And I think it's really important to have that. And it's so important that it decenters— I think I was listening to an episode recently where you talked about the white gaze and what you have to deal with all the time in trying to present things to a majority white audience. And I think it's really important for us white people to listen to this and realize that not everything is about and for us. And I mean, there are so many things in life where this is true: movies, TV shows, books and stuff. And yeah, I think it's great that that your voices are there and having these conversations, and I think that people should listen to your podcast.

AW: I appreciate that. Yeah. Because it requires a deep interrogation, a self-interrogation by white people to really deal with the feelings. Let me just step back and give the usual disclaimer. Everybody's nice. Everybody's good. Nobody's mean. Nobody is a bad person. Let me just say all that to get that out of the way, right? But what we're talking about is that when I say something on the show, when Pamela says something on the show and you get this feeling like “Wow, that doesn't feel good to me,” then you need to take some time and figure out why it is that you're feeling this way. And it's tied to your privilege, something that you need to interrogate, and it will make you a better person and for everybody.

KK: I don't know. I can't wrap my head around people, like, Zoom-bombing. This is nothing that would ever come to my mind. “You know what, I'm going to go Zoom-bomb this person.” I just…

EL: Well, I mean, it’s just a bad way to spend your time, but not everyone has the same time priorities.

AW: Well, no. So I think that's a great question. And let me just say that it that's how deep and pervasive it is in people, right, that people grow up and have this experience of being raised by other people who have ingrained within them that it is fundamentally, and in some sense, it just burns their soul to have somebody who does not look like them, have someone who is “lesser” than them take the center stage, be deemed the expert. And so again, I'm not calling these people bad. But there is something within some of us that says — and it’s called white supremacy, by the way — that we all have, that we all have to fight, that is so ingrained in some people that they feel compelled to do it. And so they, again, no one's going to fix that for them. And the person who did this to Pamela has it in spades, right? And so when we say that, so I think too often we make it an intellectual exercise, right? We say that it just makes no sense. Right? It doesn't make any sense because white supremacy makes absolutely no sense. But it is a thing. And it's there. And that's what it is, right? So I've been working a lot on calling, naming things so that we don't get confused, because as long as we don't name it, then it just gets to be out there. Like, “Oh, I don't understand.” We understand this exactly. It's called white supremacy. And we need to fight it in our discipline, and across the board.

PH: And it doesn't always just show its face via Zoom-bombing with the N-word in the chat, right? It shows up with who you invite to your podcast. It shows up with who's winning awards from our big national organizations. It shows up with who gets tenure, who even lands into a tenure track position, who even gets to go into graduate school, who actually majors as a mathematician, who actually goes to college, who actually graduates high school, who actually gets told that they're a mathematician. Right? So this is showing its ugly head in very visual ways that we all feel a huge sense of, “Oh, no, this is terrible. I'm sorry, this happened to you.” But the truth is that white supremacy is in everything within the mathematical sciences. And so you know, we got to pull it at its root, my friends. At its root!

AW: Yes.

PH: So this was just one way in which it showed itself, but I want to make it clear that it is pervasive.

KK: Sure. Right.

EL: So what I love about hosting this podcast is that we get to know both people and their math and their relationship to their math. And so we're gonna pivot a little bit now, maybe pivot a lot now, and say, Okay, what are your favorite theorems? And, yeah, I don't know who wants to go first. But, yeah, what's your favorite theorem?

KK: Yeah, let’s hear it.

PH: I’ll do it. I’ll go first. I always like hearing Aris talk. So I'm just like “Aris, go,” right? But no, I’m going to take the lead today. Alright, so I wanted to tell you about this theorem called Zeckendorf’s theorem. I don't know if you know about it.

KK: I do not.

PH: And it goes like this. So start with the Fibonacci numbers without the repeated 1. So 1, 2, and then start adding the previous two, so 3-5-8, and so on. Alright. So if you start with that sequence, his theorem says the following, if you give me any positive integer N, I can write it uniquely as a sum of non-consecutive Fibonacci numbers.

AW: Oh, wow!

EL: Uniquely?

PH: Yes. And this is why you need to get rid of the 1, 1. Because otherwise you have a choice. But yeah. So it's hard to do off the top of my head, because I'm not someone who, like, holds numbers. But say, for example, we wanted to do 20. Maybe we wanted to write the number 20 as a sum of Fibonacci numbers that are not consecutive. So what would you do? You would find the largest Fibonacci number that fits inside of 20. So in this case, it would be 13.

AW: Yeah.

PH: 13 fits in there. Okay, so we subtract 13. We're left with 7. Repeat the pattern.

KK: Ah, five and two.

KK: Five and two! They're non consecutive.

KK: Okay.

PH: Yeah.

AW: Wow!

PH: Three is in between them, and eight is in between the others. And so you can do this uniquely. And so this is using what's known as the greedy algorithm because you just do that process that I just said, and it terminates because you started with a finite number.

KK: Sure.

PH: And so the the proof, of course, there's the, you know, “Can you do it?” but then “Can you do it uniquely?” So the thing that you would do there is assume that you have two different ways of writing it, each of which uses non-consecutive, and then you would argue that they end up being exactly the same thing. So that, in fact, they use the same number of Fibonacci numbers and that those numbers are actually the exact same.

KK: Sure, okay.

EL: Yeah. Like I'm trying to figure out — and I don't, I also am not super great at working with numbers in my head just on the fly. But yeah, I'm trying to figure out, like, what would have gone wrong if I had picked eight instead of 13 to start with, or something? And I feel like that will help me understand, but I probably need to go sit quietly by myself and think about it. Because there’s a little pressure.

PH: Yeah, it's a little subtle. And it might be that you don't get big enough, you end up having to repeat something.

EL: Yeah, I feel like there's not enough left below eight to get me there without being consecutive.

PH: Yeah. Right.

AW: Right. Because you’ve got to get 12. Yeah, yes. Yeah.

KK: Yeah, it makes sense, right? Like, I guess, you know, if you pick the largest one less than your number, then it's more than halfway there. That's sort of the point, right? So that's how you prove it terminates, but also the the non-uniqueness, the non-uniqueness seems like the hard part to me somehow, but also the non-consecutive. Wait a minute, I don't know, which is.

AW: Well it sounds hard, period.

KK: Yeah. I like this theorem. This is good. What attracts you about this theorem? What gets you there?

PH: So I, in part of my dissertation, I found a new place where the Fibonacci numbers showed up. And so once you find Fibonacci numbers somewhere new, I was like, what else is known about these beautiful numbers? And so this was one of those results that I found, you know, just kind of looking at the literature. And then I later on started doing some research generalizing this theorem. So meaning, in what other ways could you create a sequence of numbers that allows you to uniquely write any positive integer in this kind of flavor, right, that you don't use things consecutively, and consecutively, really, in quotes, because you can define that differently. And so it led me to new avenues of research that then I got to do. It was the first few research projects with some of my undergraduate students at the Military Academy. And then I learned through them — they looked him up — that he actually came up with this theorem while he was a prisoner of war.

AW: Oh, wow!

PH: This is when Zeckendorf worked on this theorem. And to me, this was really surprising that, you know, my students found this out. And then I was like, “See, mathematics, you can just take it anywhere.” lLke this poor man was a prisoner of war, and he's proving a theorem in his cell.

KK: Well Jean Leray figured out spectral sequences in a German POW camp.

PH: I did not know that!

AW: Anything to pass the time.

KK: What else are you going to do?

EL: I mean, Messiaen composed the Quartet for the End of Time — I was about to say string quartet, but it's a quartet for a slightly different instrumentation, in a concentration camp, or a work camp. I'm not sure. But yeah, I'm always amazed that people who can do that kind of creative work in those environments, because I feel like, you know, I've been stuck in my house because of a pandemic, and I'm, like, falling apart. And my house is very comfortable. I have a comfortable life. I am not as resilient as people who are doing this. But yeah, that is such a cool theorem. I'm so glad that you said that. And I'm trying to think, like, Lucas numbers are another number sequence that are kind of built this way. And so is there anything that you can tell us about the the sequences that you were looking at, like, I don't know, does this work for Lucas numbers? I don't know if you've looked at that specifically, or did you look at ways to build sequences that would do this?

PH: Yeah. So we started from the construction point of view. So rather than give me a sequence, and then tell me how you can uniquely decompose a number into a sum of elements in that sequence, we worked backwards. So one of the research projects that we started with is what we called — there's a few of them — but one, it was a “Generacci” sequence. And so what we would do is, instead of thinking of the numbers themselves, imagine that you have buckets, an infinite number of buckets, you know, starting out the first bucket all the way to infinity, and you get to put numbers into the sequence in the following way. So you input the number 1 to begin with, because you need a number to start the sequence. And since you want to write all positive integers, well, you’ve got to start with 1 somewhere. So you stick the number 1 in the first bucket. And then you set up some system of rules for which buckets you can use to pull numbers from that then you add together to create new numbers. Well, you only have one bucket, and you only put the number 1 in it. So then you move to the next bucket. Well, okay, you want to build the number two, and you only have the number one, and as soon as you pull it from the bucket, you don't have any other numbers to use. So let's stick the number two in the second bucket. Oh, well, now I could maybe in my rule, grab a number from two buckets, and add them together to get the next number. Oh, that starts looking familiar. The third bucket will have not the number three, because you were able to build it. So what next number could you grab? Well, maybe you can stick in the 4 in there. And so by thinking of buckets, the numbers that you can fill the buckets with, that you couldn't create from grabbing numbers out of previous buckets under certain rules, you now start constructing a sequence. And provided that you very meticulously set up the rules under which you can grab numbers out of the buckets to add together to build new numbers, then you do not need to add that number into the buckets, because you've already built it.

EL: So what rules you have about the buckets will determine what goes in the buckets.

PH: Exactly, exactly. So you might say okay, maybe our buckets can contain three numbers. And you're not allowed to take numbers out of consecutive buckets, or neighboring buckets, or you must give five buckets in between. So what must go into the buckets to guarantee that you can create every single number and you can do so only uniquely? And so these are these bin decompositions of numbers. But you are working backwards. You start with all the numbers, and then you decide how you can place them in the buckets and how you can pull them from the buckets to add together. So I'm being vague on purpose, because it depends on the rules. And actually it's quite an open area of research, how do you build these sequences? You set up some some capacity to your bucket, some rules from where you can pull to add together. And the nice thing is that it's very accessible, and then it leads to really beautiful generalizations of these kinds of results like that of Zeckendorf.

EL: This is very cool.

AW: Fantastic.

EL: All right. So Aris, I feel like the gauntlet has been thrown.

KK: Yeah.

AW: Yeah, well mine is simple. This is not a competition. Yeah, no. I guess mine is influenced — I’ve been thinking about a bunch of different things, but I keep coming back to the same one, which I think is influenced by my identity as a teacher first and foremost when I think about the fundamental theorem of calculus. I just keep coming back to that one. And I don't know how many people have used this one with you on this podcast before, but for me, it hits so many of the check marks of my identity in terms of thinking about myself as a mathematician and a teacher, in the sense that for a lot of students who get to calculus, it's one of the first major, major theorems that will show up in their faces that we actually call out and say this is a theorem. And we call it fundamental, right? We don't often bring up the fundamental theorem of algebra in college algebra, right? Or in other places, or the fundamental theorem of arithmetic, right? But so it's one of these first fundamental theorems. And so it also helps to tell the story of a course, right? And so that really hits the teacher part of me where too often people in the calculus sequence spend all this time talking about derivatives, and all of a sudden, we just switch the anti-derivatives. And we don't really say why. You'll figure out in the next couple of sections, and then we start adding rectangles, and we don't say why. And so it really is, at least the way that the order of calculus has gone and in terms of how to teach it, in my experience, it really is this combination, like, oh, this is why we've been doing this. And this is the genius of relating two things. Sometimes I've gone in, and I've talked about, like I put up a sine curve, and a cosine curve, and we talk about how one of them measures the area under the curve. And then I pretend to bump my head and get amnesia. And then I'll come and say, “Oh, look, looks like we've been talking about derivatives. Right?” And they’re like, “Wait, what do you mean we're talking about derivatives?” “This is the derivative of this one.” And they’ll go, “What? We were measuring the area under the curve.” “Well, we’re also measuring the derivative, right?” This is the derivative, but this is measuring the area. And it's like, Oh, right, and so it's just one of these “aha” moments, where if people have been paying attention, it's like, oh, that's actually pretty cool, right? And then also in terms of the subject itself in relationship to high school, just really thinking about — because I get a lot of students who know all the rules, right? And they look at the anti-derivative with the integral sign and say “That's the integral.” Well, that's an anti-derivative, right?

EL: We’re not there yet.

AW: Yeah, that the anti-derivative and the integral are actually different. And so just having that conversation. And it also is a place to talk about the history of the subject and stuff like this.

EL: Yeah, I love it. And, at least for me, I feel like it's a slow burn kind of theorem. The first time you see it, you're like, “Okay, it's called the fundamental theorem of calculus. I guess some people think it's really important.” So that might be your Calculus I class. And then you see it again, maybe in an introductory real analysis class. And you're like, “Oh, there's more here.” And then you teach calculus, and you’re like, “Ohhhh!”

AW: Oh right, yes!

EL: Your brain explodes. You're like, “This is so cool!” And then your students are where you were several steps ago. And they’re like, “Okay, I guess it’s all right.”

AW: If I get the success rate of like, I've had three or four people go, “Whoa!” And it's like, okay, yeah, you're with me. And so this is out of hundreds of people.

EL: If you can get a few people that do that the first time they see it, that’s awesome.

AW: Yes. Yeah. No, it's been fulfilling for sure. And so then the proof itself, you know, it's also great, because then it culminates all of the theorems that you've been talking about beforehand. Depending on the proof, of course, but like, there's the intermediate value thereorem. There's the mean value theorem for integrals. There's unique continuity, at least in this version of it, in order for it to work. So yeah, it's great.

KK: So when you teach calculus, there's always two parts to the fundamental theorem. And so I like the one where the derivative of the integral is the function back, right? That's the fun, like for the mathematician in me, this is the fun part. Your students never remember that. Right? They always remember the other one, where we evaluate definite integrals by finding it the anti-derivative. So I was going to ask, if you had to pick one of the two, which one is your favorite?

AW: I mean, part of it is because at least the way that I've taught it, we're coming out of the mire of Riemann sums.

KK: Right.

AW: And so people have suffered through doing rectangles so much. And then I just get to say, “Oh, you don't have to do this anymore.” I mean, I've had a few students go, you know, now that we do — I always use the antiderivative of x squared on zero to 10, or the area under the curve of x squared from zero to 10. And like, sometimes I'll say, “Oh, that's 1000 over 3, right?” And then it was like, “Well, how did you do that so quickly?” We'll see. Right? But then, at the end, when I'll say, okay, and then we do another one again. And then I show how to apply the theorem, and people say, “Well, why didn't you just say that?” And then we have a great conversation there about how this isn't about the answer, that this is about a process and understanding the impact of mathematical ideas, that the theorem, as with all theorems, but this one is my favorite, is an expression of deep human intellect. And that if we reframe what theorems are, we get a chance to rehumanize mathematics. And so I think that too often in our math classes, and our math discourse, we remove the theorems from the humanity of the people who created them. And so people get deified, like Newton and Leibniz, but you know, these same people had to sit down and work hard at it and figure it out.

KK: No, it’s certainly a classic, but it is surprising how little it has come up on our podcast. It was the very first episode.

AW: Oh, okay.

KK: Yeah. Amie Wilkinson chose it. And then this will be episode 60-something.

AW: Okay. Yeah.

PH: Wow.

EL: We've talked, we've mentioned it in some other episodes. But it isn’t — I mean, there are just — I love this podcast, obviously, I keep doing it. And there are just so many types of theorems. And I love that you two picked different types. Yours, Aris, is one of these classics. Everyone who gets to a certain point in math has seen it, hopefully has appreciated it also. And Pamela, you picked one that none of us had ever heard of and made us say, “Whoa, that's so cool!” And people just have so many relationships with yours. And that's what this podcast is really about. Actually it's not about theorems. It's about human relationships with theorems and what makes humans enjoy these theorems. And so you picked two different ways that we enjoy theorems. And I just love that. So yeah.

KK: Yeah, that is what we're about here, actually. I mean, I mean, yeah, the theorem. But actually what I like most about our podcast, so let's toot our own horn here. We’re trying to humanize mathematics. I think everybody has this idea that mathematicians are a very monolithic bunch of weird people who just — well, in movies we’re always portrayed as either being insane, or just completely antisocial. And I mean, there’s some truth and every stereotype, I suppose, but we are people, and we love this thing. We think it's so cool. And sharing that with everyone is really what's so much fun.

AW: Yeah. And I think also that, for me, the theorem itself, and what it reveals, touches something that’s inside of us. There’s something about it, right? There’s the “Whoa” part that is that is indescribable and that I think really touches to our humanity. There is a eureka moment where you're just like, “Oh, I understand this now.” Or this connection is amazing, right? Yeah, it's indescribable.

KK: So we all agree these things are beautiful. So here's a question. Where do people lose this? I mean, I have a theory, but — because we've all had this experience, right? You're at a cocktail party and someone says, they find out you're a mathematician and like, oh, record scratch. I hate math. Okay.

AW: Yes, yes, yes.

PH: But I don’t think they hate math, though, Kevin.

KK: No, they don’t. Nobody hates math. Nobody hates math when they're a kid. That's exactly right. So I think when they say that they mean that the algebra caused them trouble. When x’s started showing up.

PH: I don't even think that's it.

KK: Okay. Good. Enlighten me because I want an answer to this that I can’t find.

PH: I don't think it's that people hate math or that they hate that the alphabet showed up all of a sudden in math that they hate how people have made them feel when they struggle with math. Math is an inanimate object. Math is not going out there and, like, punching people in the face. It's the way that people react to other people's math. Right? The second that you don't use the language in the way that somebody expects you to use it and you're trying to communicate properly and somebody says, “That’s not how you say it. It's not FOILing. It's called distributing!” Right? But you knew what I meant when I said FOIL the binomial!

KK: Of course I did.

PH: FOILing this gives you the middle term, blah, blah, right? So it’s again about human interactions. And if you make someone feel dumb, they'll never like what it is that they're trying to learn

AW: Amen to that. And they will conflate the two, which is what always happens.

PH: That’s exactly it!

AW: They will replace the experience with the subject itself, when in fact, they're talking about the experience. Yeah. So yeah, we've been working a lot about this in the last few years, Pamela and I and Dr. Michael Young, about when people say they hate mathematics, they’re really talking about their mathematical experience. So my immediate response to your question is just bad teaching. Let's just call it what it is.

PH: Right.

AW: I don't want to get on my podcast too early. We're recording later.

PH: We’re recording in a bit, yeah.

AW: But yeah, we're talking about people. And I say this as a loving critique of the greatest discipline in the history of people. I truly believe that, but I believe that the way we teach it, and the cultural norms we take with it, devalues people, and so I want every person who's listening to this now to then the next time they hear somebody say they hate it, look at them as an innocent person who had a bad mathematical experience. And then, because I see too often amongst my people in the community who say they hate having these conversations with people who say they hate it. And I think we need to return innocence back to that person. And say that this is not a person who hates you or even hates the subject. This is a hurt person. Yes, this is a person who has been damaged in our subject. And by the way, I go much farther than that. It's our responsibility to try and help repair that because this person is going to impact their cousin, their child, their relative, by bringing this hate of the subject, when in fact, it doesn't have anything to do with the subject.

EL: Yeah. It’s about the traumatic experiences. And actually, I think mathematicians often have a bit of a persecution complex and think this is the only place where people have this reaction. But one of my hobbies is singing, and in particular, singing with large groups of untrained people who are just singing because we love singing. And the baggage that people bring to singing is similar. I’m not saying it's entirely the same, but people have been made to feel like their voice isn't good enough.

AW: Yes.

EL: They have this trauma associated with trying to go out and do this sometimes. Obviously a lot of people love to sing and will do it in public. A lot of people love to sing at home and are scared of doing it in public because they're worried about, you know, their fourth grade music teacher, who told them to sing quieter, or whatever happened.

PH: Yes,

AW: That’s right. That's right. And the connection is similar, because what are we saying? We're saying that if you don't hit this right note, then it doesn't count. As opposed to if you don't get the answer seven, then we're not going to value you because the answer is seven, right? Because we have this obsession with the correct answer in mathematics. Right.

PH: And not only that, but also doing it fast.

AW: Yes.

PH: You and I have talked about this before, that — maybe in singing, this is different. I'm not sure. I definitely can relate to the trauma of never singing out loud in public. But is there this same sentiment that you must get it perfect the first time and pretend that it doesn't actually take you hours of training?

EL: I mean, it comes up. There’s definitely, people can feel more valued if they're quicker at picking things up than others, although, you know, it's not the same. There's no isomorphism between these two, I don't know, to bring a little silly math lingo in. But there definitely, there are a lot of similarities, and I think about this a lot, because two things I love in my life are math and singing with my friends. And, you know, I just see these relationships. But yeah, I could go on a whole rant, and I want to not do that.

AW: No, no, no, I appreciate you bringing it up.

EL: But I think it's a really interesting correspondence.

AW: And then the final one is that, you know, in the music space, what is it that we really should be trying to do, value everybody's voice? And in mathematics, we should be valuing everybody's contribution. Right? This is all we're saying. And what does each discipline look like when we value people's voices, no matter where they are on the keys? And we value everyone's contribution to trying to solve a problem.

EL: Yeah, yeah. And how can we help people, you know, grow in the way they want to? You can say, like, “Oh, I like I am not as good a sight reader as I want to be. How can I get better?” How can we help people grow in that way without feeling cut down?

AW: Yeah.

EL: Yeah, it is true for math, too. Yeah. It's just, everything is connected. Woo.

AW: Yes. But you know, we've been talking about, you know, these human relationships we all have with math. And so another part of our podcast that we love is forcing you to do make one more human connection between math and something else with the pairing. So what goes well, Pamela, with this theorem about uniquely writing the numbers in terms of the Fibonacci sequence?

PH: So I was trying to think about my favorite food, and when it was the epitome of perfection, and I came up with, okay, so if we're going to pair it with something to drink, I was like, I want to think about happy moments. Because this feels like a happy theorem. And so I want to go with some champagne.

KK: Okay.

PH: Okay, I was like, “We're gonna go fancy with it!” But then for food, I'm thinking about, oh, this is hilarious. So I went to a conference in Colombia, we visited Tayrona which is a beach in Colombia. And on the side of the beach, I paid to have ceviche, fresh ceviche. And I've never been happier eating anything in my life. And so I imagine myself learning Zeckendorf’s theorem at the beach in Tayrona in Colombia, with some champagne and the ceviche.

EL: Oh man.

AW: Wow.

PH: Beat that, Aris! Beat. That.

AW: There’s no way. So wait, so I want to make sure I understand. So is this while you're reading the proof? Or is this while you’re—

PH: This is like the gold standard. If I were to put all the, like, uniqueness of my favorite food, my favorite drink and my favorite theorem, I would put them in a location which is Tayrona in Colombia, at the beach, eating ceviche sipping on some champagne, learning Zeckendorf’s theorem.

AW: Okay.

KK: Is this the Pacific coast or the Caribbean?

PH: You’re asking questions I should know the answer to, and I believe it’s the Caribbean.

KK: Okay.

PH: Nobody Google that. [Editor’s note: I Googled that. It is the Caribbean.] I have no idea where they took me in Colombia. I just went.

KK: Sure.

EL: Yeah, that sounds so lovely as I look out of my window where there's snow and mud from some melted snow.

PH: Ditto.

AW: So I yeah, I think for the fundamental theorem of calculus, I think this is something that's just classic. Like you're just having a nice pizza and some ginger ale. You're just sitting down and you're enjoying something hopefully that everybody likes and that connects with everybody, that everybody hopefully sees that they get to get that far. So yeah, I mean, my daughter recently — I didn't realize this. She's 9. And we were talking. We visited my aunt in DC. My aunt raised me. And my daughter was much younger at that time, but then every time she thinks about going to visit, she thinks about the ginger ale that my aunt got her because that was the only time she ever got ginger ale. So she’s like, “Oh, I like your aunt, Daddy, because you know, I had ginger ale there.” And I was like, Oh, I should have ginger ale more often. So that made me think of that.

PH: That’s adorable.

EL: I can really relate to that feeling of, like, when you're a kid, something that is totally normal for someone else isn't what's normal for your family. So you think it's a super special thing.

AW: It’s amazing.

EL: I think I had this with, like, Rice-a-Roni or something at my aunt's house, and my mom didn't use Rice-a-Roni, and I was like, “Whoa, Mom, you should see if you can find Rice-a-Roni.”

PH: Amazing.

EL: She was like, “Yeah, they have Rice-a-Roni here.”

AW: Rice-a-Roni’s the best.

KK: I haven't had that in years. I should go get some.

AW: Me either. All right.

PH: That’s how you know you made it.

KK: You know what? You know, single mom and all that, and I lived on Kraft macaroni and cheese when I was a kid. And yeah, you would think I don't like it any more. But, aw man.

PH: Listen, that thing is delicious. So good.

AW: I was about to say.

EL: They know what they’re doing. Yeah. Well, that's great. And I mean, pizza is my favorite food. As great as ceviche on the beach sounds, pizza, just, when you come down to it, it's my favorite food. And so I love that you paired the fundamental theorem of calculus with my favorite food.

KK: So I'm curious, there must be a human who doesn't like pizza, but have you ever met one? I've never met one.

PH: No.

EL: I know people who don't like cheese. And cheese is not — I mean, to me cheese is essential to the pizza experience, but you can definitely do a pizza without cheese.

AW: Yeah. No, my wife also always says that for her it's about the sauce. So I think she might be a person who can get rid of the cheese if the sauce is right. Yeah.

KK: But the crust better be good too.

AW: Of course, of course. It's a full package here.

EL: But okay, so you say that, but on the other hand, I would say that bad pizza is still really good.

KK: Sure.

EL: I mean, you can have pizza that you're like, “I wish I didn't eat that.” But I have very rarely in my life encountered a slice of pizza that was like, “Oh, I wish I wish I had done something else other than eat that pizza.”

AW: It’s actually a pretty unbeatable combination, right? Tomato sauce, cheese and bread.

PH: Yeah. It kind of can't go wrong. Yeah.

KK: When I was when I was in college, there was a place in town. It was called Crusty’s Pizza, and I don't think it exists anymore. And it was decidedly awful. But we still got it because it was cheap. So we would occasionally splurge on the good pizza. But you could get a Crusty’s pie for like five bucks.

AW: Absolutely.

KK: This is dating myself. But yeah, absolutely. Always. All right, so we've got we've got theorems, we’ve got pairings. You've plugged your podcast pretty well, although you can talk about it more if you'd like. Anything else that either of you want to plug, websites, the Twitter?

EL: Yeah, but can you say a little more about the book that you mentioned?

AW: Yeah, the book is a series of dialogues that was an extension of an AMS webinar series that we gave about advocating for students of color mathematics. And so we had just decided, you know, there was so much momentum, we had hundreds of people coming every time to the four-part series. And so we were like, you know, we've gotten to a place where we've given all these talks, and then you give talks, create momentum, and then it just ends. And we're just like, you know, what, not this time. Let's create a product out of this. And so, we decided quickly to get the book together, just answering some of the unanswered questions from the webinar series. So we had the motivation, in terms of answering their questions. And yeah, we got it together. And it was an honor. So it really is just a list of our dialogues, a transcription of our dialogues, answering some of the unanswered questions from that webinar series. And so it's gotten some really good reviews, and people are using it in their departments. And so it's been fantastic so far.

PH: Yeah, I think that's that's the part that I'm really enjoying, getting the emails from people who have purchased the book. And so maybe I should say the full title, so it is Asked and Answered: Dialogues On Advocating For Students of Color in Mathematics. And the things that I hear from folks who have purchased the book — so thank you all so much for the support — is that they didn't expect that there is part of a workbook involved in the book. So it isn't just Aris and I going back and forth at telling you things. I mean, a lot of that there is, that is part of the content. But there's also a piece about doing some pre-reflection before we start hearing some of the dialogue that we have, and then also the post part of it. So how are you going to change? And how are you going to be a better advocate for students of color in mathematics? And so it leaves the reader with really a set of tools to come back to time and time again. That's really what I see as a benefit of the book. And people are purchasing it as a department to actually hold some kind of book club and really think about what of the things that we suggest that professors implement in their department, in their classrooms, in their institutions, what they can actually do. And so the reception has been really wonderful. And I'm just super thankful that people purchase the book, and we're supporting our future work.

EL: Yeah. And can you also mention, is it minoritymath.org, the website that hosts Mathematically Uncensored?

AW: That’s correct. That's right. So yeah, that's the home of the podcast. And that's a place where we're trying to create voices for underrepresented minorities in the mathematical sciences. And so you can go there not just for the podcast, but for other content as well that centers around that experience.

KK: Okay.

EL: Fantastic. Thank you so much for joining us.

KK: Yeah.

EL: I had a blast.

PH: Thank you.

KK: This was a really good time.

EL: Yeah. Over lunch today, I'm going to be writing down numbers and writing them in terms of Fibonacci numbers. It’s great.

AW: It will be fantastic.

PH: Awesome.

AW: Thanks.

PH: Bye, everyone.

KK: Thanks, guys.

On this very special episode, we had not one but two guests, Pamela Harris from Williams College and Aris Winger from Georgia Gwinnett College, to talk about their podcast, Mathematically Uncensored, and of course their favorite theorems. Here are some links you might be interested in as you listen to the episode.

Harris's website

Winger's profile on Mathematically Gifted and Black

Mathematically Uncensored, the podcast they cohost
Minoritymath.org, the Center for Minorities in the Mathematical Science, a website with information and resources for people of color in mathematics
Asked and Answered: Dialogues On Advocating For Students of Color in Mathematics, their book
Zeckendorf's theorem and a biography of Edouard Zeckendorf

Jean Leray, a French mathematician who worked on spectral sequences as a prisoner of war
Olivier Messiaen's Quartet for the End of Time, composed when he was a prisoner of war
A paper generalizing the Zeckendorf theorem by Harris and coauthors
Our episode with Amie Wilkinson, who also chose the Fundamental Theorem of Calculus, making it 2 for 2 among mathematicians with the initials AW.

Episode 63 - Lily Khadjavi

Evelyn Lamb: Hello, and welcome to My Favorite Theorem, the podcast from 2021. I don't know why I said that, just, it's a math podcast, and it is currently being taped in 2021. I'm your host Evelyn Lamb. I'm a freelance math writer in Salt Lake City, Utah. And this is your other host.

Kevin Knudson: Hi, I'm Kevin Knudson, professor of mathematics at the University of Florida. No, look, it's important to say it's 2021 because 2020 lasted for about six years. It was—I couldn't wait for 2020 to be over. I don't think 2021 is much better yet. It's January 5. I'll leave our listeners to figure out what's going on right now that might be disturbing. And, and yeah, but anyway, no, happy new year. And I had a very nice holiday. My son has been home for nine months now. He's going to go back to school finally next month to finish up his senior year in college. And I did nothing for a week. I mean, like when I say nothing, I mean nothing. Just get up, watch some TV, like we’re watching old reruns of Frasier, like this is the nothing levels I saw. It was fantastic.

EL: Very nice.

KK: How about you guys? Did you have a nice holiday?

EL: Um, I had a bad bike accident right before Christmas. So I had some enforced rest. But I'm mostly better now. I have gotten on my bike a couple times, and nothing terrible has happened. So still a little more anxious than usual on the bike. We were taking a ride yesterday and I could tell I was just like, not angry, but just, you know, nervous and worried. And it's just like, Okay, I'm just at the scene of the trauma, which is my bike seat, and getting over it. But I hope I will continue to not fall off my bike and keep going.

KK: That’s the only thing to do. Back in my competitive cycling days when I was a postdoc, I had some pretty nasty crashes. But yeah, you just get back on. What else are you going to do? So anyway, enough of that. Let’s talk math.

EL: Yes. And today, we are very happy to welcome Lily Khadjavi to the show. Hi, will you introduce yourself and tell us a little bit about yourself?

Lily Khadjavi: Hi. Oh, thanks, Evelyn. It's so great to be here. I'm Lily Khadjavi, as you said. I'm a professor of mathematics at Loyola Marymount University, which is in Los Angeles, California. I'm a number theorist by training, but I'd say that I'm lucky to have taken some other mathematical journeys, especially since graduate school, and I don't know, for example, this past year, maybe my biggest excitement is I was lucky to be appointed to a state board in California. So by the Attorney General, Xavier Becerra, to be appointed to an advisory board looking at policing and law enforcement and the issue of profiling. And so that's an issue that's very important to me. And it was an unexpected mathematical journey.

EL: Yeah.

LK: If you’d asked me 20 years ago, what would I be up to, I might not have thought of that. And I've taken many a bike spill in my day, so I could feel some nice affinity being here today. You’ve just got to get back on and be careful, of course.

EL: Yeah. And that that must be an especially important issue in LA, because I know the LAPD has been the subject of some, I guess, investigations and inquiries into their practices and things like that.

LK: That's exactly right. And over the years, it was under a consent decree, so an agreement between the US Department of Justice and the City of Los Angeles, with many aspects monitoring police practice. And actually, some of that included data collection efforts looking at traffic stops. And that, combined with teaching a statistics course, is what really gave me a window more into policing practice, into problems that where I wanted authentic engagement for my students with the real world and took me on, maybe I'll say unexpected journeys to law conferences and elsewhere, as I started to learn more about the issues, the ways that as mathematicians, we can bring tools to bear on on these social questions too.

EL: Yeah, very cool.

KK: Yeah.

EL: So what is your favorite theorem? And I know that's an unfair question, but I will ask it anyway. And then, you know, you can run away with it.

LK: Yeah. I know this podcast is not visual, but I'm already kind of smiling in a terrified way because I found this question so difficult, really an impossible task, because I thought it's like asking me when my favorite song—I don't know, do you have a favorite song?

EL: That is hard to say. If you asked me, I would start listing things. I would not, probably, be able to tell you one thing.

LK: What do you think, Kevin?

KK: I, uh, Taxman?

LK. Okay, I thought you would name the opening the music for the podcast as a favorite too.

EL: Oh, yeah.

LK: You know, shout out to that.

KK: I do like that. But now, you know, maybe What Is Life by George Harrison? Single?

LK: Oh, yeah. Okay, well, maybe I'll count that as listing, which is what Evelyn started to do. Because it's very, difficult.

KK: It is.

LK: You know, I was really wrestling with this. And it got me kind of thinking about why do we like certain theorems. I think I pivoted to what Evelyn said. I started wanting to make lists. And of course, it's fun to talk about things that are new to everyone. And, you know, it's been a remarkable podcast, and lots of people have staked out, I mean, they've grabbed those beautiful favorite theorems. But I started thinking, could you have a taxonomy? I really saw a taxonomy of theorems. Not by discipline. So not a topological statement or an analytic proof, but by how mathematicians feel about them, or the aesthetic of them. And so my first you know, category had to be sort of the great workhorses, like those theorems that get so much done, but they also they never cease to amaze you. And I mean, it’s hard not to point right away to the fundamental theorem of calculus, and I think maybe in your very first episode. That's right, that might be what?

KK: Yeah, Amie Wilkinson.

EL: Yes, Amie Wilkinson just came in and snatched that one. Although as everyone knows, we do double theorems, you know, we don't have a rule that you can't use the same theorem again.

LK: No, because that's one we use again and again and again. You know, even this past semester, I was teaching multivariable calculus. And you know, we have this march through line integrals, double, triple integrals, and we build, of course, to Green’s theorem, Stokes’ theorem, the divergence theorem. So these main theorems in calculus that the machinery is heavy enough for the students that even if I'm trying to put them in a context where, “Oh, this is really all the fundamental theorem of calculus,” I think that gets obscured obscured for students first trying to get their head around these theorems. Even though you relate them, you say, Oh, but they've got the boundary of this—maybe endpoints of a curve or some other surface boundary, and you're relating it as the relationship between differentiation integration, and it's so it's beautiful stuff. But I think I'm not convinced my students thought of it as the same theorem, even if I tried to emphasize this perspective. But still, they, all of us can be blown away by how powerful the theorem is in all of its incarnations. And so that's a great workhorse. So we don't have to talk at length about that one. It's been here before, but you know, you just have to tip your hat to that one. But I was wondering, are there other great workhorses something you put in that in that category?

KK: So I argue—I mean, so you mentioned the fundamental theorem—the workhorse there is actually the mean value theorem.

LK: Hmm.

KK: Because the fundamental theorem, at least for one variable, is almost a trivial corollary of the mean value theorem. And I didn't appreciate that until I taught that sort of undergraduate analysis course for the first time. And I said, “Wait a minute.” And then I sort of came up with this joke, I'm actually going to write a book. It's like a “Where's Waldo” style thing: Where's the mean value theorem? Because in every proof, it seemed like, Well, wait a minute, by the mean value theorem, I can pull this point out. Or there is one, I don't know where it is, but it's in there somewhere. So I really like that one.

LK: That’s a really great perspective. I also will say that I did not happen on that feeling until teaching analysis for the first time, of course, versus, you know, for seeing these theorems or learning about them, and even learning them in analysis, not just using them in calculus. Know, that reminds me that it wasn't till grad school, maybe taking a differentiable manifolds class, and that's not really my area. But seeing, Oh, you can define a wedge product, you can define these things in a certain way. Oh, they really are literally all the same theorem. But I like this perspective, maybe that would have been a way to convince my students a little bit more, to kind of point to the mean value theorem, because it would put them on more familiar turf too. I really like that. Yeah. Are there other workhorses?

EL: So the first one that came to my mind was classification of surfaces, in topology, of like, you know, the fact that you can do that—I feel like I it's like so internalized to me now. And yeah, I don't know, that for some reason that came to mind, but it's been a long time since I did research and was keeping up with, you know, proving things. So yeah, it’s—but yeah, I think I would say that anyway.

KK: Yeah. And I would sort of think anything with fundamental in its name right.

LK: Yeah, I was thinking that.

KK: So the fundamental theorem of arithmetic, okay, so that you can factor integers as products of primes, or the fundamental theorem of algebra, that every polynomial with complex coefficients has a root. But then more obscure things like the fundamental theorem of algebraic K-theory. You guys know that one?

LK: That one, I'm afraid does not trip off my tongue.

KK: All it is, is it's a little bit weird. It just says that the K-theory of if you have a ring, maybe it needs to be regular, that if you look at the K-theory of the ring, and the K-theory of a polynomial ring in one variable over it, they're the same. And the topological idea of that is that, you know, it's a contractibility argument somehow. And so it's fundamental in that way.

LK: These are great workhorses. Yeah. And also, Evelyn, you mentioned the classification, like these results are just so fundamental. So in whether they have fundamental in the name or not, they are.

EL: Like, naming it fundamental, it's almost like cheating that point. Or, maybe not cheating, maybe stealing everyone else's thunder. It’s like, “No, I already told you that this is the fundamental theorem of this.”

LK: My poor students, whenever I want them to conjure up the name and think of something that way, I make the same corny joke. I'm like, “It's time to put the fun back into…” and they’re like, “Ugh, now she's saying fundamental again.” So yeah, I was thinking, too, that in different fields, we reach back, even as we're doing different things in our own work, back to those disciplines that we were sort of steeped in. And I think for topologists, there are so many great theorems to reach to.

KK: Sure.

LK: But I was thinking even like the central limit theorem in statistics and probability, so this idea that you could have any kind of probability distribution—start with any distribution at all—but then when you start to look at samples, when the samples are large enough, that the mean is approximated by a normal distribution. That somehow never ceases to amaze me in the way that the fundamental theorem of calculus, too. Like, “Oh, this is a really beautiful result!” But it's also a workhorse. There are so many questions in statistics and probability that you can get at by gleaning information from the standard normal distribution. So maybe I’d put that into a workhorse category.

KK: Sure.

EL: Actually, Heine-Borel theorem, maybe could be kind of a workhorse, although I'm sort of waiting for for you to say that it's actually the mean value theorem too.

KK: No, it's just, it's just that, you know, compact sets are closed and bounded. That's it. Right?

EL: Yeah. Yeah, actually, yeah, that, once again, is such a workhorse that it's often the definition that people learn of compactness.

LK: That’s right.

EL: Like the first time they see it. Or, like such an important theorem that it it almost becomes a definition. Actually the Pythagorean theorem, in that case, is almost a definition.

KK: Sure.

EL: Slash how to measure distance in the Euclidean plane.

LK: Yeah, that's a good example. So maybe now we have so many workhorses, well, another category I was thinking of — it's beautiful stuff. I was thinking of those theorems where the subtlety of the situation kind of sneaks up on you. So maybe you hear the statement, and you kind of even think, “Oh yeah, I believe that,” like the Jordan curve theorem, I think you had a guest speak about this, too. So this, you know, idea of a simple closed curve. So you just draw it in the plane, there's an inside, and it divides the plane into an inside and outside. And I kind of really remember—I can't tell you what day of the week it was—but I remember the first time this came up in a class, and I thought, “Yeah.” But then we started thinking about how would you go about proving something like this, or even just being shown, someone drawing, a wild enough crazy curve, where suddenly you can't just eyeball it and immediately see what's inside and what's outside. So I don't know what this category or set of theorems should be, but the subtlety sneaks up on you even though statement seems reasonable.

EL: “I can't believe I have to prove this.” Maybe that’s slightly different. Well, what I mean is like, I can't believe this is a—It seems so intuitive that understanding that there is something to prove is a challenge, in addition to then proving it.

LK: Yeah. And maybe you can't even prove it—Well, how about the four color theorem? So this map coloring theorem, this idea that the four colors suffice, so if you have states or counties or whatever regions, you want to make your map of, that if they share a common edge boundary, then use different colors, that four colors is enough. I don’t know, has a human being ever proven that? My understanding is that it took computing power.

KK: It’s been verified.

EL: I think they’ve reduced the number of cases, also, that have to be done from the initial proof, but I still think it's not a human-producible proof.

KK: That’s right. But I think Tom Hales actually verified the proof using one of these proving software things. So I mean, yeah, but that was controversial.

LK: That brings up a neat question about what constitutes proof in this day and age. I've seen interesting talks about statements where, or journals where something's given as this: “Okay, here's a theorem. And here's the paper that's been refereed.” And then later, oh, here's something that contradicts it. And people are left in a sort of limbo. Well, that's another discussion, things unproven, un-theorems, I don't know. Well, anyway, in this category, that's going to help the subtlety of the situation sneaks up on you. If I start coloring maps, testing things out, after a while, I’d say, “Oh, there's a lot to this.” But the statement itself has an elegant simplicity.

KK: Well, it's not easy. So I curated a math and art exhibition at our local art museum, in the Before Times, and one of the pieces I chose was by a Mexican artist, and it's called Figuras Constructivas. And it was just two people standing there talking to each other, but it was sort of done in this—we’ve all done, you probably when you were a kid—you took a black crayon and scribbled all over a page, and then you fill in the various regions with different colors, right? It reminded me of that. And the artist used five colors. And so when I was talking about this to the to the docents, I said, “Well, why don't we create an activity for patrons to four-color this map?” So they did, they created it, because it was just a map. And they did it, and the docents were just blown away by how difficult it was to do a four-coloring. You know, five colors is fairly easy. But four was a real challenge.

LK: That sounds really fun. And what a great example of math and art coming coming together. And my understanding of the history of this, too, is that the five-color theorem was proved not just before four colors, but was kind of doable in the sense that

EL: I think it’s just not that hard.

LK: Certainly not that hard in the sense of firing up the computers and whatever else has done.

KK: Needing a supercomputer in 1976.

LK: Which is basically my phone, maybe. Well, I had another category mind, which is, theorems where the proofs are just so darn cute.

KK: Okay.

LK: And so what I was thinking of—I tried to have an example for each of these—which was the reals being uncountable.

EL: Yeah.

LK: And I think you've had guests talk about this. And you know, like a diagonalization argument, like say, just look at the reals only from 0 to 1. And suppose you claim that that is a countable set. Okay, go ahead and list them in order, in whatever ordering you've got for countability. And then you can construct a new element by whatever was in the first place of your first element, do something different in your first place, whatever was in the second place of the second element, do something different in your second place of your new element, and so on down the line. So you go along the diagonal, if you had listed these and so this, I don't know my crude description of a diagonalization argument, that you can construct a new element that wasn't in your original set and so contradict the countability. I don't know, I thought that's really cute.

EL: Yeah. And that was probably the first theorem that really knocked my socks off.

KK: Mm hmm. It's definitely a greatest hit on our show.

EL: Yeah.

LK: So I guess that’s right. We've had a Greatest Hits show, so I don't know, this taxonomies kind of disintegrating, like “Workhorses,” “Just so darn cute,” “Situation sneaks up on you.” But yeah, I don't know if there are others that fit into the “Just so darn cute.” That was the one that came to mind because I kind of wanted it on my favorites, and then I was like, “Oh, someone's already talked about this on the show.”

KK: Well, I really like—so I'm a topologist. And I really like the theorem that there are only four division algebras over the reals. So the reals, the complexes, the quaternions and the octonians. And it's a topological proof. Well, I mean, there's probably an algebraic proof. But my favorite proof is topological. So I don't know if it's cute.

EL: That isn't what you'd expect the proof of that to be, for sure.

KK: No. And it's it's sort of—I'm looking through it. So I taught this course last year, and I'm trying to remember the exact way the proof goes, not that our listeners really want to hear it. But it involves cohomology. And it's really pretty remarkable how this actually works. Oh, here it is. Oh, yeah. So it involves, it involves the cohomology rings of real projective spaces. And so if you had one of these division algebras, you look at some certain maps on cohomology, and you sort of realize that things can't happen. So I think that's very, well, I don’t know if it’s cute, but it's a pretty awesome application of something that we spend a lot of time on.

LK: Yeah, it’s so neat when a different field. So you know, we have these silos, historically: algebra, topology, and so on. So the idea that a topological proof gives you this algebraic result is already a delight, but then that's heavy machinery. That's sounds like a really neat.

KK: Or fundamental theorem of algebra, right?

LK: Well, that's when I was thinking when you started saying saying, “Oh, there's a topological proof.” I started thinking, “Oh, fundamental theorem of algebra.” You know, fire up your complex analysis. And yeah, neat stuff. Yeah.

EL: Well, and there's this proof of the Pythagorean theorem that I have seen attributed to Albert Einstein, I think, that has to do—Steve Strogatz wrote, I think, an article for The New Yorker about it. So Oh, yeah, listening to my bad explanation of it semi-remembered from several years ago, you can go read it. But it has to do basically with scaling. And it's a kind of a surprising way to approach that statement.

KK: I think it was in the New York Times [editor’s note: Evelyn was right, it’s the New Yorker! [note to the editor’s note: Evelyn is the editor of this transcript]], or it's also in his book, The Joy of X, I think it's in there too. And yeah, I do sort of vaguely remember this, it is very clever.

it's a nice one to record.

LK: Yeah, this makes me want to swing back to many things. It's also reminding me, so here we are in pandemic times. And so at the university I'm at, we're not spending time in the department, but you reminded me that when I wander around the department, sometimes we have students’ projects, or work from previous semesters, up here and there, along with other posters. And I'll look at something and say, “Oh, I haven’t thought about Pythagorean Theorem from that context, or in that way.” So just different representations of these. So maybe there should be a category where there are so many proofs that you can reach to, and they're each delightful in their own way, or people could you could start to ask people what's your favorite proof instead of a favorite theorem, maybe.

KK: I think we did that with Ken Ribet because he did the infinitude of primes. He gave us at least three proofs.

LK: And I think three pairings to boot. Yeah. Nice. I'm wondering if another, so there was the “so darn cute,” how about something where the simplicity of the statement draws you in, but then the method of the proof may just open up all kinds of other problems or techniques. So in other words, I guess what I'm saying is some theorems, we really love the result of the theorem. Maybe the Fundamental Theorem of Calculus. That result itself is so useful. But on the other hand, Fermat’s Last Theorem, I don't know if anyone's even pointed to that on the show, but something in number theory where the statement was—I mean, this is how I got suckered into number theory. That's what I would say. So you have this statement. You mentioned the Pythagorean theorem, so this idea that, that you could find numbers where the sum of two squares is itself a square, like three squared plus four squared equals five squared, but what if you had cubes instead, could you find a cubed plus b cubed equals c cubed, or any a to the n plus b to the n equals c to the n. And, you know, that's a statement that, although the machinery of number theory that's developed to ultimately prove this is so technical, and involves elliptic curves and modularity, all kinds of neat stuff, but that the statement was very simple. And of course, at some level, then it wasn't even just proving that statement. It was the tools and techniques we can develop from that. But I remember telling a roommate in college about, “Oh, there's this theorem, it's not even proven.” So that was a question too. Why are we calling this a theorem? So back in the day, that was not a theorem, but it was still called Fermat’s Last Theorem. And in telling, you know, relating the story that Fermat was writing in the margin of his I don't know Arithmetica or something in the 1600s. And that he said, “I had the most delightful proof for this, but the margin is too small to contain it.” And my roommate’s first reaction actually was “Has anyone looked through all of his papers to find the proof?” And that was nice, because, you know, coming from a different discipline, studying English and history and so on. Because to me that wasn't the first reaction. It was like, oh, if Fermat had a proof, can we figure it out too? Or can we figure out what he—maybe he had something, but what mistake might he have made? Because there's more to this one perhaps. But anyway, the category was “statements that draw you in with their simplicity.” Maybe the four-color theorem should have landed here.

EL: Yeah.

LK: I don’t know.

EL: Yeah, draw you in. It's kind of—I don't know if this is maybe a bad analogy to draw, but kind of catfishing. Yeah. There’s just this nice, well-behaved statement. And oh, yeah, now it's a giant mess to prove. Actually, maybe like the Jordan curve theorem.

LK: Yeah, maybe a lot of these end up there. Then there's that way, though, if something's finally— sometimes when you finally prove something, you're like, “Oh, why didn't I think of that earlier?” I don't know that Fermat will ever land there for me, but maybe the Jordan curve, maybe there are aspects of some of these that you just come to a different understanding on the other side of the hill.

EL: Yeah. So I think if I were doing this taxonomy, one of my categories—which is probably not a good category, but I think I would have a sentimental attachment to it and be unable to get rid of it—would be like, theorems with weird numbers in them or, or really big numbers in them, like the one that we talked about with Laura Taalman, where there’s this absurd bound for the number of Reidemeister moves you have to do for knots. Like there are some theorems where like, you've got some weirdness, it's like, oh, yeah, this theorem is, works for everything except the number 128. And it's just like, theorems with weird numbers in them, or weird numbers in their proofs, I think would be one of mine. Or, like the proof of the ternary Goldbach conjecture several years ago, which I only remember because I wrote about it, is basically proving that it works up through a certain very large number of just individual cases, and then having some argument that works above 10 to the some large number, and like, that's just a little funny. It's like, “Oh, yeah, we checked the first 12 quadrillion. And then once we did that, we were made in the shade.” And I don't know, I think I think that goes a long way with me.

KK: How about theorems with silly names? Like, like the ham sandwich theorem.

LK: I think the topologists corner the market on this, right? Yeah? No? Maybe?

KK: We really do.

LK: Yeah, the ham sandwich. No, I like so we need to find one that's like, unusual cases, or a funny number comes up and it has a funny name to boot. I love these categories. Well, how about how about something where the statement might surprise the casual listener. So in other words, like, the Brouwer fixed-point theorem, so when I’m I chatting with my students, I say, “Oh, you toss a map of California onto the table (because I'm in California) and there's some point on the map that's lying above its point in the real world.” And then oh, I can do it all over again, toss it again, it doesn't land the same way. And then, and they start to realize, oh, there's something going on here. But I don't know if that's surprising. Maybe my students are a captive audience. I say surprising to the casual listener. Maybe it's surprising to the captive audience. I don't know.

EL: Yeah, well, that's definitely like a one where the theorem doesn't seem surprising, or, you know, the theorem doesn't seem that strange. And then it has these applications or examples that it gives you that you're like, oh, wow, like that makes you think like, for me, it's always the weather. What is it? That there are two antipodal points on the earth with the same, you know, wind speed, or at any given time or temperature, whatever the thing is you want to measure?

KK: The Borsuk-Ulam theorem.

EL: Maybe the same of both? I don't remember how many dimensions you get.

KK: Well, you could do it in every dimension. So yeah, it's the Borsuk-Ulam theorem, which is that a map from the n-sphere into R^n has to send a pair of antipodal points at the same point. Right.

EL: So the theorem, when you read it, it doesn’t seem like it has anything weird going on. And then when you actually do it, you're like, “Whoa, that's a little weird.”

LK: Oh yeah, I like that. Maybe that's true, so many of the things we we look at. So I guess I realized, as I was thinking about these, I was tipping towards theorems where there's also some kind of analogy or way to convey it without the technical details. Certainly, if the category is to draw in the casual listener, or to sucker someone in without the technical machinery. Yeah, so I don't know what would be next in the taxonomy of theorems. Do you have other ideas?

EL: I’m not sure. Yeah, I feel like I’d need to sit down for a little bit. Actually first go through our archives and like look at the theorems that people have picked, and see where I think they would land.

LK: I had a funny taxonomy category that's very narrow, but it could be “guess that theorem.” But I was thinking theorems with cute names or interesting funny names that have also been proven in popular films.

KK: Oh, the snake lemma.

LK: Ding-ding-ding, we have a winner.

KK: You know, don’t pin me down on what the movie is. I can't remember.

EL: I think t's called It’s My Turn.

KK: That’s it.

LK: Wow, the dynamic duo here has exactly. And I have to admit, when I was thinking of it, I was like, “I don’t remember the movie.” And I had to look it up. But anyway, algebra comes to the rescue.

EL: Yeah, I’ve seen that scene from it, but I've never seen the rest of the movie for sure.

KK: Has anybody?

LK: As mathematicians, maybe we should.

EL: I don’t even know if it’s on DVD. It might might never have been popular enough to get to the new format.

KK: And isn’t that the last time that there's any math in the movie? Like it's this opening scene, and she proves the theorem, and then that's it? Never any more?

LK: So it's really a tragedy, that film. But no, they say this is the year that people said, Oh, they watched all of Netflix. I don't know if that's possible. So this is the year, then, to reach out to expand. Or maybe if we rise up and request more streaming options for the movie. I would like to show my students students that. Yeah, but I also admit, I haven’t seen the film.

Maybe a big core category we're missing is those theorems that really bridge different areas or topics. So Kevin, you give an example of a statement that could be algebraic, but it's proven topologically. But then I was thinking, are there theorems that kind of point to a dictionary between areas? And I only had one little example in mind, but maybe I'll call it my little unsung hero, a theorem that won't be as familiar to folks, but I was thinking of something called Belyi’s theorem, so not as well known as the others, perhaps, but that number theorists and arithmetic geometers are really interested in. And then actually, I went ahead and printed out ahead of time, these quotes of Grothendieck, who was so struck when this theorem was announced or proven because he'd been thinking along these lines, but was surprised at the simplicity of their proof. But my French is not very good, so I'm not going to read anything in French. But I don't know if you want to take a moment to talk about this theorem.

KK: Sure.

EL: Yeah.

KK: So what's the statement?

LK: Yeah, so maybe I'll say en route to the statement that number theorists and arithmetic geometers are interested in ramification, but I'm maybe I'm going to describe things in terms of covering maps, and whether you have branching over a covering so. So like, if you had a Riemann surface, you're mapping to Riemann surface, and you had a covering map, you might expect, okay, for every point down below, you'd expect the same number of preimages, or for every neighborhood down below, the same number of neighborhoods, if it's a degree D map, maybe a D-fold cover. And in fact, I remember my advisor first describing this to me by saying, if you had a pancake down below, you'd have D pancakes up above. And it really stuck in my head, frankly, because he was so precise and mathematical in his language at every moment, this was one of the most informal things I ever heard him say. Maybe he was hungry at the moment, he was thinking about pancakes. So as a concrete example where something different could happen, suppose I was mapping to the Riemann sphere, and I suppose I had a map, like I don't know, take a number and cube it, like x cubed, and started asking what kind of preimages points have. For example, x cubed equals 1, there are three roots of unity that map to 1, but something different is happening at zero, so only zero maps to zero. There's no other value that when you cube it, gives you zero. So now we no longer have, instead of a cover, maybe I'll say we have a cover, except at finitely many points. So somehow zero, and in that case, infinity, there's some point at infinity that behaves differently, but everything else has three distinct preimages. And maybe just to make a picture, let's take the interval from 0 to 1. So a little line segment, the real interval, and we could ask what its preimage looks like. And so above 1, there are three points up above. There are three roots of unity that map to 1, and on the other hand 0 was the only point that mapped to zero. And for the rest of the interval, all of those points have three preimages. So you could draw, maybe I'm picturing now a little graph on my original surface that's got a single vertex, say, at zero, and then three segments going out for each of the preimages of the real line, and ending at these three roots of unity, ending at the preimages of 1. And so now I'm not even thinking very precisely about what it looks like. I'm just picturing a graph. So I’m not worrying about how beautiful my drawing is. I just have one vertex over zero and then three branches. So what number theorists describe in terms of ramification, in this setting we might think of as branching. So these branch points. So I'm interested in saying when I have a map, say to the Riemann sphere, or number theorists might say to the projective line, I'm interested in what kind of branching is happening. And it turns out that — so now Belyi’s theorem — he realized that in the situation where you're branched over at most three points, so in the picture, we had over 0 and also infinity. I was kind of vague about what's happening at infinity. So that was two points. But if there are at most three points where branching happens, something very special is going on. So he was looking at maps from curves to the projective line. So in a nutshell, really what he proved was that a curve is algebraic if and only if there's one of these coverings that's branched at at most three points. So what is that saying? So saying a curve is algebraic? That's an algebraic statement. You're kind of saying, Well, if you had an equation for the curve — suppose I could write down an equation and then the solutions to that equation are the points of the curve — he’s saying that the coefficients have to be algebraic numbers. So they don't just have to be integers. I could have coefficients, like the square root of two could be a coefficient, or i, or your favorite algebraic number, but not pi, or e or any non-algebraic number. So that's an algebraic statement. But saying that that can happen if and only if, and now he has a map actually, from the curve, well I'm going to say from some Riemann surface to the Riemann sphere, that's branched over at most three points, that second statement is very topological. And it's actually sort of combinatorial too, because that graph I was describing earlier, people use those to kind of describe what's happening with these maps. And so the number of edges, the number of vertices, there's a lot of combinatorial information embedded in that picture. And so I don't know how much of the theorem really comes through in this oral description. But the point is, people were really surprised, including Grothendieck was surprised. He was so surprised and agitated, but excited, that he wrote a letter to the editor, and it's been published. Leila Schneps has done these amazing volumes about a topic called dessins d’enfants, or children's drawings, but I have to read a piece of this because he wrote something like “Oh, Belyi announced this very result.” So this idea, he says actually, “Deligne when consulted found it crazy indeed, but without having a counterexample at hand. Less than a year later, at the International Congress in Helsinki, the Soviet mathematician Belyi announced this very result, with a proof of disconcerting simplicity contained in two little pages of a letter of Deligne. Never was such a profound and disconcerting result proved in so few lines.” So Belyi had actually figured out not only a way to show that these maps exist, but he had a construction. And it reminds me of something you were saying earlier, Evelyn, where the construction exists, maybe it's an unwieldy construction, in the sense that if you really wanted to work with these maps, you might want to do better, and if you try to bound, something I tried to do earlier, you get these really huge degree bounds on maps that are not so practical, in a sense, but the fact that you could do it, so it was the fact not only of the existence, but also there was a constructive proof, opened the door to lots of other work that folks have done.

And maybe I just want to say I was looking — so my French is not good enough to read and translate on the fly. But this “disconcerting result” the word that was used déroutant, can also mean strange and mysterious and unsettling. So even our taxonomy could include unsettling proofs or unsettling results. But I really wanted to put this in the category of something that that bridges different areas, because this picture I was describing earlier really was just a graph with three edges and four vertices. It’s an example of what Grothendieck called, he nicknamed them dessins d’enfants, or children's drawings, the preimagesof this interval. And yeah, so this is really a topic that's caught people's imagination, and Frothendieck was thinking “Are there ways to get at the absolute Galois group?” Because these curves I mentioned were algebraic, so something behind the scenes here is purely algebraic. You can look at Galois actions on the coefficients, for example. But meanwhile, you have this topological combinatorial object. And when you apply this action, we preserve features of the graph, we preserve the number of vertices and edges and so on. Can you start to look at conjugate drawings? And so these doors opened up to these fanciful routes, but it also pointed to these bridges between areas. Maybe algebraic topology is full of these, where you have some algebraic tools, but you're looking at something topological, just things that bridge or create dictionaries between between areas of mathematics, I think are really neat. Yeah. So in the end, you could even bring a stick figure to life this way. So I described this funny-looking graph with just three edges, but you could actually draw a stick figure in this setting, labeling vertices and edges. So I'm picturing, I don't know, literally a little stick figure.

EL: Yeah.

LK: And give some mathematical meaning to it. And then through these through Belyi’s theorem, and through this dictionary, is actually related to curves and so on. And then you can do all kinds of fun things. Like I mentioned some Galois action, although I wasn't specific about it. You could start to ask, are there little mutant figures in the same family as a stick figure? Maybe there's a stick figure with both arms on one side? And is that conjugate somehow to your original, and so somehow there was something elusive about this. The proof had eluded Grothendieck. But it opened this door to very fanciful mathematics. And there's really been kind of an explosion of work over the years looking at these dessins d’enfants. It's a podcast, but I saw you nodding when I mentioned these children’s drawings.

EL: Well, that's a term I've definitely seen. And then not really learned anything about it. Because I must admit, algebraic geometry is not something that my mind naturally wants to go and think about a whole lot.

LK: There’s a lot of machinery, and actually one direction of Belyi — I said this theorem as and if and only if — but one direction was sort of known and takes much more machinery. And it was this disconcerting direction, as Grothendieck said, that actually took less somehow. Some composition of maps and keeping track of ramification, or using calculus to see where you have multiple images of points, or preimages. Yeah, in fact, Grothendieck, there was one last sentence I found, I culled from this great translation by Leila Schneps, who said, “This deep result, together with the algebraic geometric interpretation of maps, opens the door to a new unexplored world, within reach of all, who pass without seeing it.” And you know, we really don't usually see mathematicians speaking in these terms about their work. So that's something I loved. I also loved that Belyi’s proof was constructive too, because even if it creates bounds, I might not want to use, it becomes a lynchpin in other work that connects — the fact that it could be made effective, like not just that this map exists, but you can actually have some degree bound on a certain map, is a lynchpin. And maybe the funniest example takes me to a last category, which is how about theorems that may not be theorems? Like what counts as a theorem? And there's this statement called ABC conjecture. Which is—

EL: A can of worms.

LK: Yeah, so is it proven or not?

KK: It depends on who you ask.

LK: Yeah, so there’s this volume of work by Shinichi Mochizuki, it’s 500-plus pages, and he's created this, I think it was called inter-universal Teichmüller theory. And I, you know, I can't speak to it, but experts are chipping away, chipping away. And maybe it's — I don't know if it's too political to say it's in kind of a limbo. There may be stuff there. There's a lot of machinery there. And yet, do lots of people understand and sort of verify this proof? I'm not sure we're there.

KK: I mean, he’s certainly a respected mathematician. So that's what people taking it seriously. But that's right. But didn't Scholze point to one particular lemma that he thought wasn't true? And the explanations from Kyoto have not been satisfying?

LK: Yeah, I don't have my finger on the pulse. But it’s this funny thing where if you unravel a thread, does the whole thing come apart? And on the other hand, when Wiles proved Fermat’s last theorem, well, some people realized that it would need to do a little something more here. But then it happened. And it kind of was consistent with the theory to be able to sure to fill that in. Yeah. So this is — I don't know, it's exciting to me, but it's also daunting. But this ABC conjecture, so I mentioned Belyi’s theorem. So there's a paper that assuming the ABC conjecture — we don't know if we have a proof, but going back when we've still just called it a conjecture — you can imply or from that, you get so many other results in number theory that people believe to be true. And Noam Elkies has this paper ABC implies Mordell, so Faltings’ theorem, so this theorem about numbers of points on curves. And there's this, I thought this is funny. So I’ll mention this last thing, but this paper has been nicknamed by Don Zagier: Mordell is as easy as ABC. And it's kind of funny, because they're quite difficult no matter how you slice it. You've got something that's still an open problem. And then something that had a very difficult proof. So to say one thing is as easy as the other is sort of perfect. Yeah, there's much more to say about the ABC conjecture, but maybe that's a topic for My Favorite Conjecture.

EL: Yeah. Or My Favorite Mathematical Can of Worms.

KK: Yeah, yeah. Okay, so.

EL: I like this.

KK: Yeah. Well, I was going to say it might be time for the pairing.

EL: I think it is.

KK: So I think I think maybe you're going to pair something with Belyi’s theorem, but maybe not. Maybe there’s something else.

LK: Yeah, I wanted to. I feel like I didn't do justice to Belyi’s theorem, and originally, I'll admit it, I was going to say a gingerbread man because I mentioned stick figures. And so I was like, okay, pairing, well, I love food, made me think of food, made me think of a gingerbread man because of this theory of dessins, or drawings, of Grothendieck. So you can attach a meaning to this little stick figure. And maybe when you're baking, you start making funny-looking figures and those are your Galois conjugates, I don't know. But actually, you know, I was so long on this list of theorems, I'll be short. I think I just have to go with coffee too. Maybe a gingerbread man and coffee because, you know, I wanted to be clever and delicious. But instead I’m just going with coffee because, well, I drink a lot of coffee. They say mathematicians turn coffee into theorems. So can't go wrong. And during the pandemic working at home, I would say I've consumed a lot of coffee in all its incarnations. And maybe it takes me back, too. When I was first hearing about Belyi’s theorem and elsewhere, I was very lucky to have the chance to spend some time in the Netherlands because my advisor Hendrik Lenstra was spending time there, and so as students, we got to go for periods of time. It was very influential to me to be there. But there's a coffee you can get in the Netherlands, which is probably sort of cafe au lait meets latte. But it's called something like koffie verkeerd, and I'm going to mispronounce it, but it basically means messed up coffee. And that's one of my favorite coffees, coffee with, it has too much milk in it. I guess that's what messes it up. So maybe that will be my pairing, just to stick with coffee.

KK: All right. Yeah.

EL: Well, I thought you might go like a pairing for this whole taxonomy and just go with, like, the taxonomy of animals, which, you know, I feel like we didn't do a great job of like, getting theorems exactly into one category or another. And historically, that has also been true for our understanding of biology and like, how many kingdoms there are, you know, in terms of, like, animals, plants, and then a bunch of other stuff.

LK: That’s right, I'm counting on someone to hopefully listen enough to this sprawling, fanciful discussion and say, “Oh, no, no, no, here's how we should do it,” and actually come up with a decent but entertaining, I hope, taxonomy.

EL: Well, we also like to give our guests a chance to plug anything. You know, if you have a website, books or projects that you're working on, that you want people to be able to find online, feel free to share those.

LK: Yeah, that's such a gracious door that you open to everyone. And I mean, maybe I do want to say, in honor of work with collaborators, that math sent me on sort of an unusual journey, as I mentioned in the beginning. So now, for example, looking at the issue of racial profiling and statistics and policy and law. And I do think that there are ways that mathematicians are very creative and can carry that creativity to all of their endeavors, including many of us are spending a lot of time in the classroom. And so that interest has led to a collaboration with Gizem Karaali. She's at Pomona College. And so we do have some books that we've been lucky to co-edit, so many creative people have contributed to. So these are books around mathematics for social justice. There are some essays. There are contributed materials of all sorts. The first volume came out in 2019, in the Before Times. The second volume is due out in 2021. But these represent the work of so many people. And actually, many of the theorems that have come up in your beautiful podcast have come up there, like Arrow’s impossibility theorem around voting theory. Kevin, I think you've been in talks about gerrymandering. And that’s, you can imagine, a topic of great interest. And these materials are more introductory, for folks to bring into the classroom. But as I said, I think mathematicians are very creative, and so it's neat to see what other people have done. And so I hope others will be inspired by those examples as they're creating authentic engagement and cultivating critical thinking for ourselves and all the students we work with.

EL: Yeah, well we’ll make sure to put links to that in the show notes.

KK: Sure.

LK: Yeah. Well, thank you for a sprawling conversation today.

KK: This has been a sprawl, but it has been a lot of fun, actually. I kind of felt like you were interviewing us a little more.

LK: Oh, I that sounds fun to me.

KK: Yeah. This is a great one. I'm going to look forward to editing this one. This will be a good time.

LK: Well, maybe a lot will end up on the editing floor.

KK: I hardly ever cut anything out. I really don't.

LK: There’s always a first time.

EL: You’re on the hot seat!

KK: Lily, thanks so much for joining us. It's been a lot of fun.

LK Thank you for your time.

On this episode, we talked with Lily Khadjavi, a mathematician at Loyola Marymount University in Los Angeles. Instead of choosing one favorite theorem, she led us through a parade of mathematical greatest hits and talked through a taxonomy of great theorems. Here are some links you might enjoy as you listen.

Khadjavi's academic website
Her website about mathematics and social justice, which includes the books she mentioned with co-editor Gizem Karaali
Leila Shneps's book The Grothendieck Theory of Dessins d'Enfants
Steve Strogatz's article about Einstein's proof of the Pythagorean theorem

Try your hand at four-coloring Joaquin Torres-Garcia’s Figuras Constructivas
And some past episodes of My Favorite Theorem about some of the theorems in this episodes:
Adriana Salerno and Yoon Ha Lee on Cantor's diagonalization argument
Henry Fowler and Fawn Nguyen on the Pythagorean theorem
Susan D'Agostino on the Jordan curve theorem
Belin Tsinnajinnie on Arrow's impossibility theorem
Ruthi Hortsch on Faltings' theorem
Ken Ribet on the infinitude of primes
Francis Su and Holly Krieger on Brouwer's fixed point theorem

Episode 62 - Tai-Danae Bradley

Evelyn Lamb: Welcome to my favorite theorem, a math podcast. I'm Evelyn Lamb, one of your hosts. And here's your other host.

Kevin: Hi. I’m Kevin Knudson, professor of mathematics at the University of Florida. It's been a while. I haven't seen your smiling face in a while.

EL: Yeah. I've started experimenting more with home haircuts. I don't know if you can see.

KK: I can. It's a little a little longer on top.

EL: Yeah.

KK: And it's more of more of a high and tight thing going here. This is Yeah. All right. It looks good.

EL: Yeah, it's been kind of fun. And, like, depending on how long ago between washing it, it has different properties. So it's very, it's like materials science over here, too. So a lot of fun.

KK: Well, you probably can't tell, but I've gone from a goatee to a plague beard. And also, I've let my hair grow a good bit longer. I mean, now that I'm in my 50s, there's less of it than there used to be. But I am letting it grow longer, you know, because it's winter, right?

EL: Oh yeah. Your Florida winter. It's probably like, what? 73 degrees there?

KK: It is 66 today. It's chilly.

EL: Oh, wow. Yeah, gosh! Well, today we are very happy to invite Tai-Danae Bradley to the podcast. Hi, Tai-Danae. Will you tell us a little bit about yourself?

Tai-Danae Bradley: Yeah. Hi, Evelyn. Hi, Kevin. Thank you so much for having me here. So I am currently a postdoc at X. People may be more familiar with his former name, Google X. Prior to that, I recently finished my PhD at the CUNY Graduate Center earlier this year. And I also enjoy writing about math on a website called math3ma.

EL: Yes, and the E of that is a 3 if you're trying to spell it.

TDB: Yeah, m-a-t-h-3-m-a. That's right. I pronounce it mathema. Some people say math-three-ma, but you know.

EL: Yeah, I kind of like saying math-three-ma my head. So, I guess, not to not to sound rude. But what does X want with a category theorist?

TDB: Oh, that's a great question. So yeah, first, I might say for all of the real category theorists listening, I may humbly not refer to myself as a category theorist. I'm more of, like, an avid fan of category theory.

KK: But you wrote a book!

TDB: Yeah, I did. I did. No, I really enjoy category theory, I guess I'll say. So at X, I work on a team of folks who are using ideas from—now this may sound left field—but they're using ideas from physics to tackle problems in machine learning. And when I was in graduate school at CUNY, my research was using ideas in mathematics, including category theory, to sort of tackle similar problems. And so you can see how those could kind of go hand in hand. And so now that I'm at X, I'm really just kind of continuing the same research interest I had, but, you know, in this new environment.

EL: Okay, cool.

KK: Very cool.

EL: Yeah, mostly, we've had academics on the podcast. We’ve had a few people who work in other industries, but it's nice to see what's out there, like, even a very abstract field can get you an applied job somewhere.

TDB: Yeah, that's right.

EL: Yeah, well, of course, we did invite you here to talk about your job. But we also invited you here to ask what your favorite theorem is.

TDB: Okay. Thank you for this question. I'm so excited to talk about this. But I will say, I tend to be very enthusiastic about lots of ideas in mathematics at lots of different times. And so my favorite theorem or result usually depends on the hour of the day. Like, whatever I’m reading at the time, like, this is so awesome! But today, I thought it'd be really fun to talk about the singular value decomposition in linear algebra.

KK: Awesome!

TDB: Yeah. So I will say, when I was an undergrad, I did not learn about SVD. So I think my undergrad class stopped just before that. And so I had to wait to learn about all of its wonders. So for people who are listening, maybe I could just say it's a fundamental result that says the following, simply put. Any matrix whatsoever can be written as a product of three matrices. And these three matrices have nice properties. Two of them, the ones on the left and the right, are unitary matrices, or orthogonal if your matrix is real. And then the middle matrix is a diagonal matrix. And the terminology is if you look at the columns of the two unitary matrices, these are called the singular vectors of your original matrix. And then the entries of the diagonal matrix, those are called the singular values of that matrix. So unlike something like an eigen decomposition, you don't have to make any assumptions about the matrix you started with. It doesn't have to have some special properties for this to work. It's just a blanket statement. Any matrix can be factored in this way.

EL: Yeah, and I, as we were saying, before we started recording, I also did not actually encounter this in any classes.

KK: Nor did I.

EL: And yeah, it’s something I've heard of, but not never really looked into because I didn't ever do linear algebra, you know, as part of my thesis or something like that. But yeah, okay, so it seems a little surprising that there aren't any extra restrictions on what kind of matrices can do this. So why is that? I don't know if that question is too far from left field.

TDB: Maybe that's one of the, you know, many amazing things about SVD is that you don't have to make any assumptions. So number one, in mathematics, we usually say multiplying things is pretty easy, but factorizing is hard. Like, it's hard to factor something. But here in linear algebra, it's like, oh, things are really nice. You just have this matrix, and you get a factorization. That's pretty amazing. I think, maybe to connect why is that—to connect this with maybe something that's more familiar, we could ask, what are those singular vectors? Where do they come from? Or, you know, what's the proof sketch of this?

EL: Yeah.

TDB: And essentially, what you do is you take your matrix, you multiply it by its transpose. And that thing is going to be this nice real symmetric matrix, and that has eigenvectors. And so the eigenvectors of that matrix are actually the singular vectors of your original one. Now, depending on like, if you multiply them the transpose of the matrix on the left or right, that will determine whether, you know, you get the left or right singular vectors. So, you might think that SVD is, like, second best: “Oh, not every matrix is square, so, we can't talk about eigenvectors, oh, I guess singular vectors will have to do.” But actually, it's like picking up on this nice spectral decomposition theorem that we like. And I think when one looks out into the mathematical/scientific/engineering landscape, and you see SVD sort of popping up all over the place, it's pretty ubiquitous. And so that sort of suggests it’s not a second-class citizen. It's really a first-class result.

EL: Yeah. Well, that's funny, because I did, when I was reading it, I was like, “Oh, I guess this is a nice consolation prize for not being an invertible square matrix, is that you can do this thing.” But you're telling me that that was—that’s not a good attitude to have about this?

TDB: Well, yeah, I think SVD, I wouldn't think of it as a consolation prize, I think it is quite something really fundamental. You know, if you were to invite linear algebra onto this podcast and ask linear algebra, what its favorite theorem is, just based on the ubiquity and prevalence of SVD in nature, I'd probably bet linear algebra would say singular value decomposition.

EL: Yeah, can can we get them next?

KK: Can we get linear algebra on? We’ll see. Okay, so I don't know if this question has—it must have an answer. So say your matrix is square in the first place. So you could talk about the eigenvalues, and you do this, I assume the singular values are different from the eigenvalues. So what would be the advantage of choosing the singular values over the eigenvalues, for example?

TDB: So I think if your matrix is square, and symmetric, or Hermitian, then the eigenvectors correspond to the singular vectors.

KK: Okay, that makes sense.

TDB: But, that's a good question, Kevin. And I don't have a good answer that I could confidently go on record with.

KK: That’s cool. Sorry. I threw a curveball.

TDB: That’s a great question.

KK: Because then singular values are important. The way I've always sort of heard it was that they sort of act like eigenvalues in the sense that you can line them up and that the biggest one matters the most.

TDB: Exactly, exactly. Right. And in fact, I mean, that sort of goes back to the proof that we were talking about. I was saying, oh, the singular vectors are the eigenvectors of this matrix multiplied by its transpose. And the singular vectors turn out to be the square roots of the eigenvalues of that square matrix that you got. So they're definitely related.

KK: Okay. All right. Very cool. So what drew you to this theorem? Why this theorem in particular?

TDB: Yeah, why this theorem? So this kind of goes back to what we were talking about earlier. I really like this theorem because it's very parallel to a construction in category theory.

KK: Yes.

TDB: Maybe people find that very surprising. We're talking about SVD. And all of a sudden, here's this category theory, curveball.

EL: Yeah, because I really do feel like linear algebra almost feels like some of the most tangible math., and category theory, to me, feels like some of the least tangible.

KK: So wait, wait, are you going to tell us this is the Yoneda lemma for linear algebra?

TDB: No. Although that was going to be my other favorite theorem. Okay, so I'm excited to share this with you. I think this is a really nice story. So I'm going to try my best because it can get heavy, but I'm going to try to keep it really light. But I might omit details, but you know, people can maybe look further into this.

So to make the connection, and to keep things relatively understandable, let's forget for a second that I even mentioned category theory. So let’s empty our brains of linear algebra and category theory. I just want to think about sets for a second. So let me just give a really simple, simple construction. Suppose we have two sets. Let's say they're finite, for simplicity. And I'll call them a set X and a set Y. And suppose I have a relation between these two sets, so a subset of the cartesian product. And just for simplicity, or fun, let’s think of the elements of the set X as objects. So maybe animals: cat, dog, fish, turtle, blah, blah. And let's also think of elements in the set Y as features or attributes, like, “has four legs,” “is furry,” “eats bugs,” blah, blah, blah. Okay. Now, given any relation—any subset of a Cartesian product of sets—you can always ask the following simple question. Suppose I have a subset of objects. You can ask, “Hey, what are all the features that are common to all of those objects in my subset?” So you can imagine in your subset, you have an object, that object corresponds to a set of features, only the ones possessed by that object. And now just take the intersection over all objects in your subset? That's a totally natural question you could ask. And you can also imagine going in the other direction, and asking you the same question. Suppose you have a subset of features. And you want to know, “Hey, what are all of the objects that share all of those features in that subset I started with?” A totally natural question you could ask anytime you have a relation.

Now, this leads to a really interesting construction. Namely, if someone were to give me any subset of objects and any subset of features, you could ask, “Does this pair satisfy the property that these two sets are the answers to those two questions that I asked?” Like, I had my set of objects and, Oh, is this set of features that you gave me only the ones corresponding to this set of objects and vice versa? Pairs of subsets for which the answer is yes, that satisfy that property, they have a special name. They're called formal concepts. So you can imagine like, oh, the concept of, you know, “house pet” is like the set of all {rabbits, cats, dogs}, and, like, the features that they share is “furry,” “sits in your lap,” blah, blah, blah. So this is not a definition I made up, you know, you can go on Wikipedia and look at formal concept analysis. This is part of that. Or you can usually find this in books on lattice theory and order theory. So formal concepts are these nice things you get from a relation between two sets.

Now, what in the world does this have to do with linear algebra or category theory, blah, blah, blah? So here's the connection. Probably you can see it already. Anytime you have a relation, that’s basically a matrix. It's a matrix whose entries are 0 and 1. You can imagine a matrix where the rows are indexed by objects and the columns are indexed by your features. And there's a 1 and the little x little y entry if that object has that feature and 0 otherwise.

KK: Sure.

TDB: And it turns out that these formal concepts that you get are very much like the eigenvectors of that 0-1 matrix multiplied by its transpose. AKA, they're like the singular vectors of your relation. So I'm saying it turns out—so I'm kind of asking you to believe me, and I'm not giving you any reason to see why that should be true—But it's sort of, when you put pen to paper paper and you work out all of the details, you can sort of see this. But I say it's like because if you just do the naive thing, and think of your, your 0-1 matrix as a linear map, like as a linear transformation, you could say, okay, you know, should I view this as a matrix over the reals? Or maybe I want to think of 0 and 1 as you know, the finite field with two elements. But if you try to work out the linear algebra and say, oh, formal concepts are eigenvectors, it doesn't work. And you can sort of see why that is. we started the conversation with sets, not vector spaces. So this formal concept story is not a story about linear algebra, i.e., the conversation is not occurring in the world of linear algebra. And so if you have mappings—you know, from sets of objects to sets of features—the kind of structure you want that to preserve is not linearity, because we started with sets. So we weren't talking about linear algebra.

So what is it? It turns out it's a different structure. Maybe for the sake of time, it's not really important what it is, or if you ask me, I'll be happy to tell you. But just knowing there's another kind of structure that you'd like this map to preserve, and under that right sort of context, when you're in the right context, you really do see, oh, wow, these formal concepts are really like eigenvectors or singular vectors in this new context.

Now, anytime you have a recipe, or a template, or a context, but you can just sort of substitute out the ingredients for something else, I mean, there's a bet that category theory is involved. And indeed, that's the case. So it turns out that this mapping, this sort of dual mapping from objects to features, and then going back features to objects, that, it turns out, is an example of adjunction in category theory. So there's a way to view sets as categories. And there's a way to view mappings between them as functors. And an adjunction in category theory is like a linear map and its adjoint, or like a matrix and its transpose. So in category theory, an adjunction is — let me say it this way, in linear algebra, an adjoint is defined by an equation involving an inner product. Linear adjoint, there's a special equation that your map and its adjoint must satisfy. And in category theory, it's very analogous. It's a functor that satisfies an “equation” that looks a lot like the adjoint equation in linear algebra. And so when you unravel all of this, it's almost like Mad Libs, you have, like, this Mad Lib template. And if you erase, you know, the word “matrix” and substitute in the whatever categorical version of that should be, you get the thing in category theory, but if you stick in “matrix,” oh, you get linear algebra. If you erase, you know, eigenvectors, you get formal concepts, or whatever the categorical version of that is, but if you if you have eigenvectors, then that's linear algebra. So it's almost like this mirror world between the linear algebra that we all know and love, and like, Evelyn, you were saying, it's totally concrete. But then if you just swap out some of the words, like you just substitute some of the ingredients in this recipe, then you recover a construction in category theory, and I am not sure if it's well known — I think among the experts in category theory it is — but it's something that I really enjoy thinking about. And so that's why I like SVD.

EL: So I think you may have had the unfortunate effect of me now thinking of category theory as the Mad Libs of math. Category theorists are just going and erasing whatever mathematical structure you had and replacing it with some other one.

KK: That’s what a category is supposed to do, right? I mean, it's this big structure that just captures some big idea that is lurking everywhere. That's really the beautiful thing, and the power, of the whole subject.

TDB: Yeah, and I really like this little Mad Lib exercise in particular, because it's kind of fun to think of singular vectors as analogous to concepts, which could sort of maybe explain why it's so ubiquitous throughout the scientific landscape. Because you have this matrix, and it’s sort of telling you what goes with what. I have these correlations, maybe I organize them into a matrix matrix, I have data and organize it into a matrix. And SVD sort of nicely collects the patterns, or correlations, or concepts in the data that's represented by our matrix. And, I think, Kevin, earlier you were saying how singular values sort of convey the importance of things based on how big they are. And those things, I think, are a little bit like the concepts, maybe. That’s sort of reaching far, but I think it's kind of a funny heuristic that I have in mind.

KK: I mean, the company you work for is very famous for exploiting singular values, right?

TDB: Exactly. Exactly.

KK: Yep. So another fun part of this podcast is we ask our guests to pair their favorite theorem with something. So what pairs well with SVD?

TDB: Okay, great question. I thought a lot about this. But I, like, had this idea and then scratched it off, then I had another idea and scratched it off. So here's what I came up with. Before I tell you what, I want to pair it pair this with, I should say, for background reasons, this, Mad Libs or ingredients-swapping recipe-type thing is a little bit mysterious to me. Because while the linear algebra is analogous to the category theory, the category theory doesn't really subsume the linear algebra. So usually, when you see the same phenomena occurring a bunch of places throughout mathematics, you think, “Oh, there must be some unifying thread. Clearly something is going on. We need some language to tell us why do I keep seeing the same construction reappearing?” And usually category theory lends a hand in that. But in this case, it doesn't. There's no—in other words, it's like I have two identical twins, and yet they don’t, I don’t know, come from the same parents or something.

KK: Separated at the birth or something?

TDB: Yeah. Something like that. Yeah, exactly. They’re, like, separated to birth, but you're like, “Oh, where are their parents? Where were they initially together?” But I don't know that, that hasn't been worked out yet. So it's a little bit mysterious to me. So here it is: I'm going to pair SVD with, okay. You know, those dum-dum lollipops?

KK: Yeah, at the bank.

TDB: Okay. Yeah, exactly. Exactly. Just for listeners, that’s d-u-m, not d-u-m-b. I feel a little bit—anyway. Okay, so the dum-dum lollipops, they have this mystery flavor.

KK: They do.

TDB: Right, which is like, I can't remember, but I think it's wrapped up with a white wrapper with question marks all over it.

EL: Yeah.

TDB: And you're letting it dissolve in your mouth. You're like, well, I don't really know what this is. I think it’s, like, blueberry and watermelon? Or I don't know. Who knows what this is? Okay. So this mystery that I'm struggling to explain is a little bit like my mathematical dum-dum lollipop mystery flavor. So, you know, I like to think of this as a really nice, tasty mathematical treat. But it's shrouded in this wrapper with question marks over it. And I'm not quite really sure what's going on, but boy, is it cool and fun to think about!

EL: I like that. Yeah, it's been a while since I went to the bank with my mom, which was my main source of dum-dum lollipops.

TDB: Same, exactly. That's funny, with my mom as well.

EL: Yeah. That that's just how children obtain dum-dums.

KK: Can you even buy them anywhere? I mean, that’s the only place that they actually exist.

EL: I mean, wherever, bank supply stores, you know, get a big safe, you can get those panic buttons for if there's a bank robber, and you can get dum-dum lollipops. This is what they sell.

TDB: That’s right.

KK: No, it must be possible to get them somewhere else, though. When I was a kid trick-or-treating back in the 70s, you know, there would always be that cheap family on the on the block that would either hand out bubblegum, or dum-dums. Or even worse, candy corn.

EL: I must admit I do enjoy candy corn. It's not unlike eating flavored crayons, but I’m into it. Barely flavored. Basically just “sweet” is the flavor.

KK: That’s right.

EL: Yeah, well, so actually, this raises a question. I have not had a dum-dum in a very long time. And so is the mystery flavor always the same? Or do they just wrap up some normal flavor?

KK: Oh, that’s a good question.

EL: Like, it falls off the assembly line and they wrap it in some other thing. I never paid enough attention. I also targeted the root beers, mostly. So I didn't eat a whole lot of mystery ones because root beer is the best dum-dum.

KK: You and me! I was always for the root beer. Absolutely.

EL: And butterscotch. Yeah.

TDB: Oh, yeah. The butterscotch are good. So Evelyn, I was asking that same question to myself just before we started recording. I did a quick google search. And I think what happens, at least in some cases, like maybe in the past—and also don't quote me on this because I don't work at a dum-dum factory—but I think it was like, oh, when we're making the, I don't know, cherry or butterscotch flavored ones, but then the next in line are going to be root beer or whatever, we’re not going to clean out all of the, you know, whatever. So if people get the transition flavor from one recipe into the other, we’ll just slap on the “mystery.” I don't know, someone should figure this out.

KK: Interesting.

EL: I don't want to find out the answer because I love that answer.

KK: I like that answer too.

EL: I don't want the possibility that it's wrong, I just want to believe in that. That is my Santa Claus.

KK: And of course, now I’m thinking of those standard problems in the differential equations course where you’re, like, you're doing those mixing problems, right? So you've got, you know, cherry or whatever, and then you start to infuse it with the next flavor. And so for a while, there's going to be this stretch of, you know, varying amounts of the two, and then finally, it becomes the next flavor.

TDB: Exactly.

EL: Well, can you quantify, like, what amount and which flavor dominates and some kind of eigenflavor? I'm really reaching here.

TDB: I love that idea.

EL: Yeah. Oh, man. I kind of want to eat dum-dums now. That’s not one of my normal candies that I go to.

TDB: I know, I haven't had them for years, I think.

KK: Yeah, well, we still have the leftover Halloween candy. So this is, we can tell our listeners—What is this today? It's November 19?

EL: 19th, yeah.

KK: Right. So yeah, we bought one bag of candy because we never get very many trick-or-treaters anyway. And this year, we had one small group. And so we bought a bag of mini chocolate bars or whatever. And it's fun. We have a two-story house. We have a balcony on the front of our house. So this group of kids came up and we lowered candy from our balcony down. When I say “we” I mean my wife. I was cooking dinner. But we still have this bag. We're not candy-eaters. But you're right. I'm jonesing for for a dum-dum now. I do need to go to the bank. But I feel a little cheap asking for one.

EL: Yeah. I feel like, you know, maybe 15, 16, is where you kind of start aging out of bank dum-dums.

KK: Yep, yeah. Sort of like trick-or-treating.

EL: Well, anyway, getting back to math. Have we allowed you to say what you wanted to say about the singular value decomposition?

TDB: Yeah. I mean, I could talk for hours about SVD and all the things, but I think for the sake of listeners’ brains, I don't want to cause anyone to implode. I think I shared a lot. Category theory can be tough. So I mean, it appears in lots and lots of places. I originally started thinking of this because it cropped up in my thesis work, my PhD work, which not only involved a mixture of category theory, but linear algebra for, essentially, things in quantum mechanics. And so you actually see these ideas appear in sort of, you know, “real-world” physical scenarios as well. Which is why, again, it was kind of drawing me to this mystery. Like, wow, why does it keep appearing in all of these cool places? What's going on? Maybe category theory has something to say about it. So just a treat for me to think about.

EL: Yeah. And if our listeners want to find out more about you and follow you online or anything, where can they look?

TDB: Yeah, so they can look in a few places. Primarily, my blog mathema. com. I'm also on Twitter, @mathema as well, Facebook and Instagram too.

EL: And what is your book? Please plug your book.

TDB: Thank you. Thank you so much. Right. So I recently co-authored a book. It’s a graduate-level book on point-set topology from the perspective of category theory. So the title of the book is Topology: A Categorical Approach. And so this is really—we had in mind, sorry about this with John Terilla, who was my PhD thesis advisor, and Tyler Bryson, who is also a student of John at CUNY. And we really wrote this for, you know, if you're in a first-semester topology course in your first year of graduate school. So basic topology, but we were kind of thinking, oh, what's a way to introduce category theory that’s sort of gentler than just: “Blah. Here’s a book. Read all about category theory!” We wanted to take something that people were probably already familiar with, like basic point-set. Maybe they learned that in undergrad or maybe from a real analysis course, and saying, “Hey, here's things you already know. Now, we're just going to reframe the thing you already know in sort of a different perspective. And oh, by the way, that perspective is called category theory. Look how great this is.” So giving folks new ways to think and contemplate things they already know, and sort of welcoming them or inviting them into the world of category theory in that way.

KK: Nice.

EL: Yeah. So definitely check that out if you're interested in—the way you said like “Blah, category theory” —he other day, for some reason, I was thinking about the Ice Bucket Challenge from, like, I don't know, five or six years ago, where people poured the ice on their head for ALS research. (You’re also supposed to give money because pouring ice on your head doesn't actually help ALS research.)

TDB: Right.

EL: But yeah, it's like this is an alternative to the Ice Bucket Challenge of category theory.

TDB: That’s right. That's a great way to put it. Exactly.

EL: Yeah. Well, thank you so much for joining us. It was fun.

KK: This was great fun. Yeah.

On this episode, we had the pleasure of talking with Tai-Danae Bradley, a postdoc at X, about the singular value decomposition. Here are some links you might find relevant:

Bradley's website, math3ma.com
Her Twitter, Facebook, and Instagram accounts

The book she co-wrote, Topology: A Categorical Approach

Episode 61 - Yoon Ha Lee

Evelyn Lamb: Hello, and welcome to My Favorite Theorem, coming at you from the double hurricane part of 2020 today. I mean, I'm not near the Gulf Coast so it's it's not quite as relevant for my life, but that is the portion of the year we are in right now. I am one of your hosts, Evelyn Lamb. I'm a freelance math and science writer in Salt Lake City, Utah. And here's your other host.

Kevin Knudson: Hi. I’m Kevin Knudson, professor of mathematics at the University of Florida. It's just hot here. But you know, there have been, like, fire tornadoes, right, in California? This is all very on-brand for 2020. This year can’t end soon enough.

EL: Yeah, we say that. I feel like I've said that at the end of many previous years, and then it's not great.

Yoon Ha Lee: As a science fiction writer, I have to say never assume it's the worst. It can always get worse.

EL: Yes.

KK: Right, right, right.

EL: Yes. And that is our guest, Yoon Ha Lee. So yeah, would you like to introduce yourself, tell us a little bit about yourself, and maybe talk about your writing a little bit, how you got to writing from the degrees that you have in math.

YHL: So my name is Yoon Ha Lee. I'm from Houston, and I'm a science fiction and fantasy writer. I actually went to Cornell to get a degree in history, and then I realized that history majors starve on the street. So I switched to math, so that I could have an income and ended up not becoming a mathematician. My best-known books are probably the Machineries of Empire trilogy, which is Ninefox Gambit, Raven Stratagem and Revenant Gun. It's space opera, lots of ships blowing up everywhere. And then a kid's book, Dragon Pearl, which is out from Disney Hyperion in the Rick Riordan Presents series. And that one is also a space opera, because ships blowing up is just fun.

EL: Yeah, well, and that's funny. I think I just put together—I had seen the Rick Riordan publishing imprint before, and I just started reading Percy Jackson the other day. And so it's like, oh, that's who that guy is.

KK: And I think I might be the only one among us who is old enough to have seen the biggest space opera, Star Wars, in the theater in its first release.

YHL: Yeah, my parents let me see it on the television when I was six years old, and I was terrified at the point where Luke gets his hand cut off.

KK: That’s Empire.

YHL: I think the second one? I forget which movie it was, but he gets his hand cut off and I had nightmares for weeks. And I'm like, Mom and Dad, Why? Why? Why did you think this was an appropriate movie for a six-year-old? And then I got all the storybooks and I wanted the lightsaber and everything, so I guess it worked out.

KK: Of course, yeah. Well, my movie story—we’re getting off track, but it's it's a good movie story. So when I was six years old, in 1975, my parents thought it would be a good idea to take me to the drive-in to see Jaws. And I had nightmares for months that there was a shark living under my bed, a huge shart that was going to get me.

EL: My husband was born I think right around the time one of them was released. I don't remember which one now. But we were talking with one of his colleagues one time and figured out that on the day he was born, that colleague was going to see that movie, like, the day it came out.

KK: I’m going to guess it was I'm gonna guess it was Jedi. I don't know exactly how old you guys are. But that's that's my guess.

EL: That sounds right. Yeah, I'm not a big star wars person. But yeah, I guess I've always not been sure, like, “space opera.” The term is something that I feel like I know it when I see it. But I don't really know, like, how to describe it. Is it just—do you feel like a categorization of space opera is, like, ships blowing up?

YHL: Ships blowing up, generally bigger, larger-than-life characters, larger-than-life stakes, big galactic civilization types of things. It's basically the Star Wars genre.

EL: Yeah

KK: It works.

EL: yeah. And the Machinery of Empire—the reason that I invited you on here is because I just read Ninefox Gambit a few weeks ago and just thought, you know, this person sure uses a lot of math terms for a novel! So mathematicians might be especially interested in reading this one, it has shenanigans with calendar systems that are based on math and arithmetic and stuff. So yeah, that was fun. So you, in addition to getting a bachelor's degree in math, you got a master's in math education, right?

YHL: Yes, at Stanford. And I ended up not using it for very long. I was a teacher for, like, half a year before I left the profession.

EL: Okay, and was it just that your writing was taking off and you wanted to do that more? Were there other reasons?

YHL: A kid came along. That was the big reason. Yeah.

EL: Oh. Yeah. That definitely can take a lot of time.

KK: Ah yeah, just a little bit.

EL: Well, that's great. So what is your favorite theorem?

YHL: My favorite theorem is Cantor's diagonalization proof. And I discovered it actually in high school as a footnote in Roger Penrose’s The Emperor's New Mind. It was really just sort of a sidelight to the extremely complicated and hard-to-follow argument that he was making in that book on the nature of consciousness and quantum physics, which, as a high schooler, you know, it basically went over my head. But I was sitting there staring at this footnote and going “I don't understand this at all.” He said in the footnote that Cantor had proven that the real numbers, the set of real numbers, has a cardinality greater than the set of natural numbers. And of course, I was a high schooler. I hadn't had a lot of math background. So my understanding of these concepts was very, very shaky. But he said if you make a list of, you know—pretend that you have a list of all the real numbers and you put them, you know, 1, 2, 3, 4, you put them in correspondence with the natural numbers, and then you go down diagonally, first digit of the first number, second digit of the second number, third digit of the third number, and so on. And then you shift it by one. So if the numeral in that place is two, it becomes three, if it's nine, it becomes zero, and so on. So you can construct a number that is not on the list, even though your premise is that you have everything on the list. And I think this was the first time that I really understood what a proof by contradiction was. My math teachers had attempted very hard to get this concept into my head. And it just did not go through until I read that proof and meditated upon it. And it's funny, because I spent most of my life as a kid thinking that I hated math. And yet there I was in the library reading books about math, so I guess I didn't hate it as much as I thought I did.

EL: Yeah, I was thinking a high schooler reading that Penrose book is definitely—yeah, you had some natural curiosity about math, it sounds like.

KK: Yeah, I'm sort of sort of surprised that your high school teachers were trying to teach you proofs by contradiction. That's kind of interesting. I don't remember seeing any of that until I got to university.

YHL: I don't know that they got into depth about it. But this was at Seoul Foreign School, which was a private, international school in South Korea. And they tried to make the curriculum more advanced, with mixed results.

KK: Sure. It’s worth a shot.

EL: Yeah, and this, this is really one of those Greatest Hits. Like if you're putting together the like, record that you're going to send out or something, like, Math’s Greatest Hits with would include this diagonalization argument. It's so appealing. And we've had another guest select that too, Adriana Salerno a few months ago and yeah, just people. I think a lot of people who eventually do become mathematicians, this is one of those first moments where they feel like they really understand some some pretty high-concept math kind of stuff. So did you see this this proof later in school?

YHL: No. Ironically, most of what I was interested in doing when I did my undergraduate degree was abstract algebra. So I didn't even take a set theory course at all. But I knew it was sort of out there in the water, and I don't know, one of the things I loved about math and that led me to switch my major to math was the idea that there were these beautiful ideas and these beautiful arguments, and just sort of the elegance of it, which was very different from history, where—I love history, and I love all the battles and things, like the defenestration of Prague and all the exciting things happening. But you can't really prove things in history. Like you can't go back and run the siege of Stalingrad again, and see what happens differently.

KK: Maybe we could though, right? We have the computing power now. Maybe we could do that. This sounds like your next novel, right? So simulation of Stalingrad, and this time, the Nazis win or something? I don't know.

YHL: Oh no. I mean, science fiction writers totally do that. There's this whole strand of alternate history, science fiction or fantasy. Harry Turtledove is one author who, he likes to have the story where aliens invade during World War II and then the Nazis and the allies have to have to team up against the aliens kind of stories there. There is a set there is a readership for these things. Sure.

EL: So you use a lot of math concepts in your writing, your fiction writing. So have you ever tried to work in diagonalization, or this kind of idea, into any of your stories?

YHL: This one? No. I mean, occasionally, I remember writing a story in college, actually, called Counting the Shapes. And it was just everything in the kitchen sink, because I was taking point-set topology, and so I used it as a metaphor for a kind of magic that worked that way, and other ideas, like, I don't know, I had recently read James Gleick’s Chaos. So I was really interested in chaos theory and fractals. And I don't know that I was super systematic about it, and I sort of suspect that a real mathematician would look at it and poke holes. You know, I'm using this as a magic system, not as rigorous math, more as a metaphor, I guess, or flavor.

KK: Oh, but I mean, writers do that all the time, right? So I, I taught math and lit class with a friend of mine in languages a few years ago. And, you know, Borges, for example, you know, this sort of stuff is all over his work, these ideas of infinity and, and it's even embedded in Kafka and all this stuff, and it can be a wonderful way to to get your readers to think about something from a point of view they might not have thought of before.

YHL: Well, the interesting thing about Ninefox Gambit and the math terminology that I used for flavor is that 20 publishers turned the book down because they said it had too much math. And I my joke about this is that they saw the word diagonalization in the linear algebra matrix context, and they didn't know what that meant, and they ran away from it. Which was extremely discouraging when my agent at the time, Jennifer Jackson, and I were going out on submission with this book. And it's like, it's basically a space opera adventure where people blow each other up. You don't have to worry about the occasional math term. It's just there as flavor for the magic system. But a lot of people—I’m sure you have encountered the fact that a lot of people in the US have math phobia, and this really does affect the readership as well.

KK: Really?

EL: Yeah, that’s funny, because in some way, I mean, you definitely use the the math language to give a certain flavor to the system that this universe is in, but you could sub it out for, like, any Star Trek term,

YHL: Exactly.

EL: t’s just like, oh, yeah, you could put tricorders and dilithium crystals, or, you know, anything in to serve that that because you know, you're it's not a math textbook, no one's learning linear algebra from reading Ninefox Gambit.

YHL: No, exactly. I actually, when I was originally writing the book, like the rough draft, I had my abstract algebra textbooks out and ready to go. And I was going to construct sort of a game engine, a combat engine of how these battles were going to work in an abstract algebra sense. And my husband who, he's not afraid of math, he's actually a gravitational astrophysicist, and he's arguably better at math than I am. But he sat me down and said, “Yoon Ha, you can't do this. You're not going to have any readers because science fiction readers who want to read about big spaceships blowing each other up do not want to have to wade through a math textbook to get to the action.” And I mean, it turned out that he was absolutely correct. So I ended up not doing that and just using it as, you know, “the force,” except with math flavor.

KK: Linear algebra is the force. All right!

EL: That’s so interesting. I noticed on your website that you have a section for games. So do you also like to design games?

YHL: I do design games. And by design games, I mean tiny little interactive, interactive fiction text adventures or really small tabletop RPGs in the indy sense. You know, three page games for five people, no GM, that kind of thing. So I do enjoy doing that. And it is related to math, I think, but it's certainly not something that we learn to do in any of our math classes.

EL: Yeah, well, I mean, personally, I think it would be very cool. Have you have you written up this potential game, the abstract algebra game thing into an actual game? Or was that kind of abandoned on the editing floor while you were putting the book together?

YHL: It got abandoned on the editing floor. Also because it would have been a tremendous time suck. And, you know, it would have been a fun idea. But if I wasn't going to use it in a book, and it certainly wasn't going to be used in like a computer game or some something like that, there just didn't seem to be enough incentive to go ahead and do it.

EL: Yeah, probably the market of math mathematicians who read sci fi is, you know, not a tiny market but maybe not quite the demographic you're looking for. But I'm just imagining, like, hauling out the Sylow theorems to, like, explode someone’s battle cruiser or something. Just saying that, you know, if you were bored some time and wanted to sink a bunch of time into that.

YHL: if somebody else wrote it, I would definitely buy it and read it, I have to say.

KK: All right. The challenge is out there, everybody. Everybody should get on this.

EL: Yeah, very cool. Yep.

KK: So another thing we do on this podcast is we ask our guests to pair their theorem with something. So what pairs well, with Cantor's diagonalization argument?

YHL: Waffles.

KK: Waffles? Oh, well, yeah.

YHL: Because sort of that grid shape. I know, this is super visual. But the waffles I'm thinking of, my husband did his postdoc at Caltech, so we lived in Pasadena. And when we were there, there was this delightful Colombian hotdog place. And they also made the best waffles with berries and fruit and syrup and whipped cream. And those are the waffles I think of when I think of the diagonal slash proof.

KK: Right. And so the grid is actually fairly small. Is it one of those waffle makers?

YHL: Yeah.

KK: Yeah. Okay, so I have a Belgian waffle maker, and it's fine. It makes four at a time, but those holes are pretty big. Right? I'm thinking of, like, the small, Eggo style, right? You can put a lot of digits.

EL: You could also, like, I guess, maybe a berry is too big to fit in them, but I'm just thinking you can put different things in all of them, make sure no two waffles have the same arrangement of syrup and berries and cream.

KK: This is a good pairing. I'm into this one a lot.

YHL: I’m hungry now.

KK: Yeah.

EL: Yeah. I just had lunch, so for once I don't leave this ravenous. So would you like to let people know where they can find you online?

YHL: Online I’m at yoonhalee.com. I'm also on Twitter as @deuceofgears and also on Instagram as @deuceofgears.

KK: Deuce of gears. Is there a story there?

YHL: It’s the symbol of the crazy general in Ninefox Gambit. Okay. And also, because I'm Korean, there are five zillion other Yoon Ha Lees. So by the time I joined Twitter, all the obvious permutations of Yoon Ha Lee had already been taken, so I had to pick a different name.

EL: Yeah, and if I'm remembering correctly, there are sometimes cat pictures on your Twitter feed. Is that right?

YHL: Yes. So the thing that I post periodically to Twitter is that my Twitter feed is 90% cat pics by volume. There are people who, you know, they tweet about serious things, or politics, or so on, and these are very important, but I personally get stressed out really easily so I figure people could use an oasis of cheerful cat pictures.

EL: Yes, I just wanted to make sure our listeners have this vital information that if they are running low on cat pictures, this is a place they can go. It's definitely been an important part of my mental health to make sure to look at plenty of cat pictures during this—these stressful times as they say.

KK: Yeah, on Instagram, I follow a lot of bird watching accounts. So I just get a feed of birds all day. It's better for my mental health.

EL: Well maybe Yoon’s cat would like that,

KK: I suspect yes, that's right. That's right. Yep.

EL: Yeah, we were talking to a friend who said that they have some bird feeders outside, they just have indoor cats. And the cats will meow to get them to open the windows in the morning so they could watch the birds outside. It’s like, “Mom, turn on the TV.”

YHL: I tried putting on a YouTube video of birds, and my cat was just completely indifferent to the visuals. But she kept looking at the speaker where the bird sounds were coming from.

KK: Hmm.

EL: Interesting. I guess maybe hearing is like more of a dominant sense or something? Cats have pretty good vision, though, I think.

YHL: Yeah, I think she's just internalized that nothing interesting comes out of the moving pictures.

EL: Yeah. Well, thanks for joining us. I really enjoyed talking with you.

KK: This has been good.

YHL: It’s been an honor.

On this episode of My Favorite Theorem, we were happy to talk with Yoon Ha Lee, a sci-fi and fantasy writer with a math background, about his favorite theorem, Cantor's proof of the uncountability of the real numbers. Here are a few links to things we mentioned in the episode:
Yoon Ha Lee's website, Twitter account, and Instagram account

Our episode with Adriana Salerno, who also loves this theorem
Roger Penrose's book The Emperor's New Mind

James Gleick's book Chaos
Harry Turtledove

Episode 60 - Michael Barany

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast for your quarantine life. I'm Kevin Knudson, professor of mathematics at the University of Florida. And here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a freelance math and science writer in beautiful Salt Lake City, Utah.

KK: Yeah.

EL: How are you, Kevin?

KK: I'm okay. I had my—speaking of quarantines, I had my COVID swab test this morning.

EL: How was it?

KK: Well, you know, about as pleasant as it sounds. But yeah, I'm sure you've been to the pool and gotten water up your nose. That's what it feels like.

EL: Yeah.

KK: And then it's over. And it's no big deal. I should have the results within 48 hours. It’s part of the university's move to get everybody back to campus, although I don't expect to go back to the office in any serious way before August. But this is late May now for our listeners, who will probably be hearing this in December or something, right?

EL: Yeah. Who even knows? Time has no meaning.

KK: Hopefully this will all be irrelevant by the time our listeners hear this. [Editor’s note: lolsob.] We'll we'll have a vaccine and everything. It will be a brave new world and everything be fine.

EL: It’ll be a memory of that weird time early in year.

KK: That’s right. The before times. So anyway, today, we are pleased to welcome Michael Barany. Michael, why don’t you introduce yourself and let us know who you are and what's up.

Michael Barany: Hi. So I'm a historian of mathematics. I'm super excited to be on this podcast. I feel like I've been listening long enough that the Gainesville percussionists must be in grad school by now.

KK: No. One of them is my son, and he just finished his third year of college.

MB: Okay, yeah. So older than he was anyway.

EL: Yeah.

MB: Yeah, so I’m a historian of mathematics. I'm based at the University of Edinburgh, where I'm in a kind of interdisciplinary social science of science and technology department. So I get to teach students from all over the university how to think about what science means when you step back and look at the people involved and how they relate to society, how ideas matter, how technology's changed the world, all that fun stuff that gets people to really rethink their place in the world and the kind of things they do with their science.

KK: That’s very cool.

EL: And I know some people who are historians of math will get a degree through a math department and some get it through a history department, I assume. And which are you? I always wonder what the benefits are of each approach.

MB: Yeah, that's great. History of mathematics is a really strange field. It’s actually, as a field, a lot older than history of science as a field, and even older than history as a profession.

EL: Huh.

MB: So history of mathematics started as a branch of mathematics in the early modern period. So we're talking like the 1500s, 1600s. There are always debates about what you classify as this or that. And it started as a way of trying to understand how mathematical theories came about, how they naturally fit together. The idea was that if you understood how mathematical theories emerged, you could come up with better mathematical theories, and you could understand the sort of natural order of numbers and the universe and everything else that you want to understand with mathematics. And then more toward the 19th and the 20th century, there are all these different variations of history of mathematics that branched out of fields like history and philosophy, and philosophy of science and history of science. So my undergrad training was in mathematics. My PhD is from a history department, but from a history of science program in that department. But it's possible to get a PhD in history of mathematics from a mathematics department, it's possible to sort of straddle between different departments. And it makes it a really rich and interesting field. Mathematics education departments or groups sometimes give PhDs in history of mathematics. And they really use the history for different purposes. So if your goal is to make mathematics better, you're taking the perspective of someone doing it from a mathematics department. If your goal is to become a better educator, then you can use history for that in a math education context. I tend to do history as a way of understanding how things fit together in the past and trying to make sense of social values and social structures and ideologies and ideas and how those fit together. And that's the approach that that you come at from a history or history of science perspective.

KK: Very cool. And How did you end up in Edinburgh of all places?

MB: Well, so the academic job market is bad enough in mathematics, right, but in history of mathematics, in a good year, there may be two to three openings in history of science jobs in general. So that's the cynical answer. The more idealistic answer is Edinburgh has this really important place in the sociology of science. In the 1970 s and 80s especially, there was this group of kind of radical sociologists in at the University of Edinburgh who sat down. It was called the Edinburgh School of the sociology of scientific knowledge, which is known for this sort of extreme relativism and constructivism view of how politics and ideology shape scientific knowledge. And I did a master's degree in that department many years later, in 2009-2010, sort of getting my feet wet and starting to learn that discipline. And that approach has been really formative for me and my scholarship. And so it was an incredible stroke of luck that they just happened to have an opening in my field while I was on the market. And I was even even more lucky to have the chance to go there.

KK: Wow, that's great. I’ve always wanted to go there. I've never been to Edinburgh,

MB: It’s the most beautiful city in the world.

KK: Yeah, it looks great. All right, well, being a historian of math, you must know a lot of theorems. So the question is, do you actually have a favorite one? And if so, what is it?

MB: So my favorite theorem is more of a definition. But I guess the theorem is that the definition works.

KK: Okay, great.

EL: That works.

MB: Which, actually—saying what it means for a definition to work is actually a really hard problem, both historically and mathematically. So it's interesting in that regard. Ao the definition is the definition of the derivative of a distribution.

KK: Okay.

MB: So distributions, as you’ll recall from, from analysis—I guess, grad analysis I is usually when you meet them.

EL: Yeah, I think it wasn't until grad school for me at least.

KK: I don't know if I've ever met them, really.

MB: So distributions were invented in 1945, more or less. And in the early years, actually, people were saying you could teach this as a replacement for your basic calculus. So the idea was, this would be something that even beginning college students or even high school students would be learning. So it's interesting to see how they have people pitched that the level of a theory or the the relevant audience, and that's part of the story, too. But in earlier stages of one's calculus education, you learn that there are functions that are integrable but not continuous; continuous but not differentiable; differentiable but not continuously differentiable, and so on. And so a big problem is how do you know something's differentiable when you're studying a differential equation or trying to prove some theorem that involves derivatives. And distributions were the kind of magic wand that was invented in the middle of the 20th century to say that's not actually a problem. Basically, if you pretend everything's differentiable, then all the math works out. And when it really is differentiable, you get the correct differentiable answer, and when it's not, then you get another answer that's still mathematically meaningful. But it's sort of your magic passphrase to be able to ignore all of those problems.

So a distribution is this replacement for a function. Where functions have these sort of different degrees of differentiability, distributions are always differentiable and they always have antiderivatives, just like functions do, but every distribution can be differentiated ad nauseam for whatever differential equation you want to do. And the way you do that is through this definition—my favorite definition/theorem—which is you use integration by parts. So that's a technique you use in calculus class, too, as a sort of trick for resolving complicated integrals. And distributions actually don't tend to look at the things that make the calculus problems challenging or interesting, depending on what kind of student you are, or what kind of teacher you are. So you set them up in a way where you don't have to worry about boundary conditions, you don't have to worry about what the antiderivative things are, because you're working with things where you already know what the antiderivative is. And the definition of distribution uses this fact from integration by parts that you essentially move the derivative from one function to another. So we don't have an exact way of saying functionally what the derivative of a distribution is. You can still say if you multiply it by a function that's super-smooth and over a bounded domain—so you don't have any boundary conditions to worry about, and so you always know how to differentiate that—if you multiply that by a distribution, and take the integral, then if you want to take the derivative of that distribution, integration by parts says you can instead throw in a minus sign and take the derivative of that smooth function instead. And so using that kind of trick, of moving the derivative onto something that is always differentiable, you can calculate the effect of differentiating a distribution without ever having to worry about, say, what the values of of that distribution are after you’ve taken the derivative, because distributions are often things that don't have sort of concrete values in the way that we expect functions to have.

EL: And I hope this question isn't very silly. But when you think about integration by parts—you know, if you took calculus at some point and learned this, there's the UV, and then there's the minus the integral of something else. And so for this, we just choose a function that would be zero on the boundary, and that would get rid of that UV term. Is that right?

MB: Exactly? Yeah. So the definition of distribution sets up this whole space of really nice smooth functions. All of them eventually go to zero, and because you're always integrating over the entire domain, and it's always zero when you go far enough out into the domain, those boundary terms with that UV in the beginning just completely disappear, and you're just left with the negative integral, and then with the derivative flopped over.

EL: All right, great. So if anyone was worried about where their UV went, that's where it went. It was zero. Don't worry. Everything's okay. Yeah. Okay. So what is good about this? Or what do you like about this?

MB: Yeah. So I think this is a really interesting definition from a lot of different perspectives. One thing that I've been trying to understand in my research about the history of mathematics is what it means for mathematics to become a global discipline in the 20th century, so to have people around the world working on the same mathematical theory and contributing to the same research program. And this definition is really helped me understand what that even means and how to understand and analyze that historically. So we think, well, you know, a mathematical theory or a mathematical idea is the same wherever you look at it, and whoever's doing it. As long as they can manipulate the definitions or prove the theorem, it shouldn't matter where they are. But if you look historically, at actual mathematicians doing actual mathematics, where they are makes a huge difference in terms of what methods they're comfortable with, how they understand concepts, how they explain things to each other, how they make sense of new techniques. I mean, learning a new mathematics technique is actually really hard in a lot of cases. And so the question is, how do you form enough of an understanding to be able to work with someone who you can't go and have a conversation with over tea the next day to sort of work out your problems? And the answer is, basically, you use things like this definition and take something you're really comfortable with—integration by parts—and give it a new meaning. And by taking old meanings and reconfiguring them and relating them to other meanings, you make it possible for everyone to have their own sorts of mathematical universes where they're building up theories, but to interact in a way where they can all sensibly talk to each other and develop new ideas and share new ideas. So that's one of the things that that's really exciting about that the definition to me.

One of the other things is sort of how do you know what the significance of the definition is? I mean, a lot of people early on said, isn't this just like a pun? Isn't this just wordplay? Quite early on, when Schwartz was sharing this definition, and some people were getting really excited about it. Some people said, well, you know, it's a cool idea. But isn't this just basically integration by parts? What's new? What's interesting about this? And the history really shows this debate, almost, between people with different kinds of values and philosophies and goals for mathematics, for mathematics education, for the relationship between pure and applied mathematics, where they take different ideas of what's really going on with this definition. Is it something that's complex and difficult and profound and important in that way, or is it something that is utterly trivial and simple, and therefore really useful to people who may be, say, electrical engineers who are trying to work with the Heaviside calculus, and need some sort of magic way to make that all add up? And what made distributions and this definition really powerful is it could be these multiple things to multiple people. So you can have mathematicians in Poland, or in Manchester, or in or in Argentina come to these very, almost diametrically opposed views of what it is that's significant or challenging or easy about distributions, and they can all agree to talk to each other and agree that it's worth sharing their theories and inviting them to conferences, and reading their publications, and they can somehow all make a community out of these different understandings.

KK: I’ve never thought about the sociological aspects in that way. That's really interesting. So the theorem that basically says that this definition is a good one. Is that a difficult theorem to prove?

MB: So there are a lot of different parts. It’s not—I guess it doesn't even boil down to one statement.

KK: Yeah, sure. Yeah, that makes sense. Yeah.

MB: So there's the aspect that when you're dealing with a function, but dealing with it using the distributions definition, that anything you do is not going to ruin what's good about it being a function. So anything you do with a distribution, if you could have done it as though it were a regular function, you get the same answer. So that's one aspect of the theorem that sort of establishes this definition. Another aspect is that distributions are, in some sense, the smallest class of objects that includes functions where everything that is a normal function can be indefinitely differentiated. So that's one way of arguing that distributions are sort of the best generalization of functions, and this competition—I mean, there are a lot of different competing notions, or competing ideas for how you can solve this problem of differentiating functions that were circulating in the 1930s and 1940s. And distributions won this competing scene, in part by the aspects of the theorems about the definition that show it’s sort of the most economical, the simplest, smallest, the best in that sense. And then you have all the usual theorems of functional analysis, like everything converges as you expect it to; if you start with something that's integrable, you're not going to lose interpretability, in some sense.

EL: So this might be a little bit of a tangent, and we can definitely decide not to go down this path. But to make this really concrete—so when I think of a distribution, the example I think of—it’s been a while since I've thought of distributions actually, is the Dirac delta function. I naturally just call it a function, but it is really a distribution. And so this is a thing that, I always think of it, it's something that you can't really define what its value is, but it has a convenient property that if you integrate it, you get 1. Like, its area is 1 even though it's supported on only one point, and it is infinitely tall. And so zero times infinity, we want it to be 1 right here.

MB: And magically it turns out to be 1.

EL: Yeah. And basically, if you decide that this function, this distribution, has this property, then things work out, and it's great. Was that before or after Schwartz? Did this definition—was this kind of grandfathered into being a distribution? Or was it the inspiration?

MB: I love how you put that. Yeah. So this, this phrase that you said at the beginning, we call it a function, but it's really a distribution. I mean, that's evidence of Schwartz’s success, right? The idea that what it really is, what it fundamentally is, is a distribution rather than a function, that's the result of this really sort of deliberate—I mean, it's not it's not an exaggeration to call it propaganda in the second half of the 1940s by people like Laurent Schwartz and Marston Morse and Marshall Stone and Harald Bohr and all of these far-traveling advocates for the theory—to say, you think you've been working with functions, you think you've been working with measures, you think you've been working with operator calculus if you're an electrical engineer, for instance. Or you think you've been working with bra and ket, with Dirac calculus for quantum mechanics, but what you've really been doing ultimately, deep down without even knowing it, is working with distributions. And their ability to make that argument was part of their way of justifying why distributions were important. So people who had no problem just doing the math they were doing with whatever kind of language they were doing, all of a sudden, these advocates for distribution theory were able to make it a problem that they were doing this without having the kind of conceptual apparatus that distributions provided them. And so they were both creating a problem for old methods and then simultaneously solving it by giving them this distribution framework.

So, they did this to the Heaviside calculus, which is about 50 years older than distributions. They did this to the Dirac calculus, where the Dirac function comes from, which comes out of the 1920s and 30s. They did this to principal value calculus, which is also an interwar concept in analysis. Even among Schwartz's contemporaries, there were things like de Rham currents, which were—had Schwartz not come along, we would all be saying the Dirac function is really a de Rham current rather than a Schwartz distribution. But then there were even things that came after distributions, or sort of simultaneously and after, that Schwartz was able to successfully claim. Like there was this whole school of functional analysis and operator theory coming out of Poland associated with Jan Mikusiński. Where Schwartz was—because he was able to get this international profile so much more quickly and effectively—he was able to say all of this really clever research and theorems that Mikusiński is coming up with, that's a nice example of distribution theory, even though Mikusiński would have never put that in those terms. So a huge part of this history is how they're able to use these different views of what a distribution really is to sort of claim territory and grandfather things in and also sort of grandchild things, or adopt things into the theory and make this thing seem much bigger than the actual body of research that people who considered themselves distribution theorists themselves were doing.

EL: Okay. And so I think we also wanted to talk a little bit about—you mentioned in your email to us, I hope I'm getting this I'm not getting this confused with anything—how this theory goes with the history of the Fields Medal.

MB: Oh, exactly. Yeah. So this was a really surprising discovery, actually, in my research. I didn't set out—the Fields Medal kind of became one thing, one little bit of evidence that Schwartz was a big deal. I never expected in my research to come across some evidence that really changed how I understood what the Fields Medal historically meant. And this was just a case of stumbling into these really shocking documents, and then having built up all of this historical context to see what their historical implications were. So Schwartz was part of the second ever class of Fields Medalists in 1950. The first class was in 1936, then there's World War II, and then they sort of restart the International Congresses of Mathematics after the war. And Schwartz is selected as part of that second class. The main reason he's part of that class is because the chair of that committee is Harald Bohr, who is the younger brother of Niels Bohr. Actually, in the early 1900s, Harald Bohr was the more famous Bohr because he was a star of the Danish Olympic soccer team.

KK: Oh!

EL: Wow!

MB: He was a striker. His PhD defense had many, many, many more soccer fans that mathematicians. He was this minor Danish celebrity. And he went on to be a quite respectable mathematician. He had his mathematics institute alongside his brother's physics institute in Copenhagen. And during the interwar period especially, he established himself as this safe haven for internationally-minded mathematics in this period of immensely divisive conflict among different national communities. And because he kind of had that role as this respected figure known for internationalism, he was selected by the Americans who organized the 1950 Congress at Harvard to chair the Fields Medal committee. And Bohr, shortly before being appointed to that committee, had encountered Schwartz in a conference that was sponsored by the Rockefeller Foundation and took place in Nancy in France, and he was just totally blown away by this charming, charismatic young Frenchman with this cool-sounding new theory that seemed like it could unite pure and applied mathematicians, that could be attractive to mathematicians all over the world. And so Bohr basically makes it his mission between 1947 and 1950 to tell the whole world about distributions. So he goes to the US and to Canada, and he writes letters all around the world, he shares it with all his friends. And when he gets selected to chair this committee, what you see him constantly doing in the committee correspondence is telling all of his colleagues on the committee what an exciting future of mathematics Schwartz was going to be.

So the problem is, then sort of the question is, what is the Fields Medal supposed to be for? And they didn't really have a very clear definition of what are the qualifications for the medal. There was a kind of vague guidance that Fields left before he died. The medal was created after John Charles Fields’ death. And there was a lot of ambiguity over how to interpret that. So the committee basically had to decide, is this an award for the top mathematicians? Is this award an award for an up-and-coming mathematician? How should age play a factor? Should we only do it for work that was done since the last medal was awarded? A long time to consider there, so that didn't really narrow it down very much in in their case. And they go through this whole debate over what kinds of values they should apply to making this selection. And ultimately, what I was able to see in these letters, which were not saved by the International Mathematical Union, which hadn't even been formed at the time, they were kind of accidentally set aside by a secretary in the Harvard mathematics department. So they weren't meant to be saved. They just were in this unmarked file. And what those letters show is that Bohr basically constructs this idea of what the metal is supposed to be for in a strategic way to allow Schwartz to win. So there's this question, there's this kind of obvious pool of candidates, of outstanding early- to mid-career mathematicians, including people like Oscar Zariski and André Weil, and Schwartz's eventual co-medalist, Atle Selberg. And they are debating the merits of all of these different candidates, and basically, Bohr selects an idea of what the Fields Medal is for, to be prestigious enough to justify giving it to this exciting young French mathematician, but not so prestigious that he would have to give it to André Weil instead, who everyone agreed was a much better mathematician than Schwartz, and much more accomplished and much more successful and very close in age. He was about five years older than Schwartz.

KK: He never won the Fields Medal.

MB: And he never won the Fields Medal, right. And so what you see in the letters from the early years of the Fields Medal is actually this deliberate decision, not just by the 1950 committee, but I was also able to uncover letters for the 1958 Committee, where they consider whether the award should be the very best young mathematicians, and they deliberately decide in both cases that it shouldn't be, that that would be a mistake, that that would be a misuse of the award. Instead, they should give it to a young mathematician, but not a young mathematician that was already so accomplished that they didn't need a leg up.

EL: Right.

MB: And that was my really surprising discovery in the archives, that it was never meant to crown someone who was already accomplished, and in fact, being accomplished could disqualify you. So Friedrich Hirzebruch in 1958, everyone agreed was the most exciting mathematician. He was in his early 30s, sort of a very close comparison to like someone like Peter Scholze today. So already a full professor at a very young age, with a widely-recognized major breakthrough. And they considered Hirzebruch, and they said, No, he’s too accomplished. He doesn't need this medal. We should give it to René Thom or someone like that.

EL: Yeah. And, of course, people like me, who only were aware of the Fields Medal once they started grad school in math—I wasn't particularly aware of anything before that—Think of it as the very best mathematicians under 40 because it has sort of morphed into that over the intervening decades.

MB: Yeah. And one of the cool side effects is now you can now put an asterisk next to—Jean-Pierre Serre is known to brag about being the youngest-ever fields medalist. But the asterisk is that he won in a period when it was still a disqualification to be too accomplished at a young age.

KK: Yeah, but he still won.

MB: He did still win. He’s still a very important mathematician.

KK: You sort of couldn’t deny Serre, right?

MB: Well, they denied Weil, right?

KK: They did. But I think Serre is probably still—Anyway, we can argue about— we should have a ranking of best mathematicians of the ‘50s, right?

EL: I mean, yeah, because ranking mathematicians is so possible to do because it’s a well-ordered set.

KK: That’s right.

EL: Obviously in any field of life, there's no way to well-order people. I shouldn't say any field. I guess you can know how fast people can run some number of meters under certain conditions or something. But in general, especially in creative fields, it's sort of impossible to do. And so how do you choose?

MB: That’s what I love about studying the sociology of science and technology, is that you get these tools for saying—you know, even in fields like running, we think of sprinting as this thing where everyone has a time and that's how fast they are. But look at all of the stuff the International Olympic Committee has to do for anti-doping and regulating what shoes you can wear, like there are all of these different things that affect how fast you are that have to be really debated and controlled. They're kind of ultimately arbitrary. So even in cases like that, you know, it seems sort of more rankable than mathematics or art or something, and you can tell a great sprinter from someone like me who can barely run 100 meters. But at the same time, there are all of these different social and technical decisions that are so interrelated that even things that seem super objective and contestable end up being much more socially determined.

EL: Yeah.

KK: Yeah. All right. So part two of this podcast is you have to pair your theorem with something, or your definition or whatever we're going to call it your distribution, whatever it is.

EL: Yeah. If you treat it as a distribution, it’ll work fine.

KK: That’s right.

MB: Exactly.

KK: So what have you chosen to pair with distributions?

MB: So what I thought I would pair distributions with is a knock-knock jokes.

KK: Okay.

MB: So I did a little bit of research before coming on here, and I basically found there are no good math knock-knock jokes. I mean, someone please prove me wrong, like tweet at me. And yeah, tell me tell me.

KK: Are there good knock knock jokes, period?

EL: Oh, definitely.

MB: Yeah. So I did come up with one that sort of at least picks up on some of the historical themes. So Knock, knock.

KK and EL: Who’s there?

MB: Harold.

KK and EL: Harold who?

MB: Harold is the concept of a function anyway?

That's the best I could do.

EL: Okay.

MB: So why knock-knock jokes? They involve puns. So you're talking about shifting the meaning of something to come up with something new. They're dialogical: there’s a sort of fundamental interactive element. They sort of make communities. So sharing a knock-knock joke, getting a knock-knock joke, finding it funny or groan-inducing, tells you who your friends are, and who shares your sense of humor. And yeah, they fundamentally use this aspect of wordplay to to make something new and to make something social. And that's exactly what the theory of distributions does and what that definition does, just sort of expand your thinking. And they're also sort of seen as kind of elementary, or basic. It's kind of like a kid's joke.

EL: Right.

MB: It’s this question of distributions as this fundamental theory, your basic underlying theory. So I think it sort of brings together all of those aspects that I like about the definition.

KK: You thought hard about this. This is a really thoughtful, excellent pairing. I like this.

EL: Yeah, I like it. I'm trying to figure out what is the analogy to my favorite knock-knock joke, which is the banana and orange one, right, which is classic.

MB: It’s the only one I use in real life.

KK: Sure.

EL: It’s a great one!

KK: Yeah.

EL: Fantastic. But, like, what distribution is this knock-knock joke?

KK: The Dirac function, right? Excuse me, the Dirac distribution.

MB: Yeah. Aren't you glad I didn't say the Dirac distribution? Yeah, no, it's the only one you actually use all the time. Yeah, the Dirac distribution, or there's that theorem that any partial differential equation can be resolved as the sum of derivatives of these elementary distributions. That's your go-to ubiquitous, uses a pun, but uses in a way that kind of makes sense and is kind of groan-inducing, but also you just love to go back and to use it over and over and over again.

KK: Right.

EL: Nice.

KK: I think back in the 70s—dating myself here—I had a book of knock-knock jokes, and it actually had the banana and orange one in it. I mean, it's like, this is how basic of a book this was. So I might be ragging on knock-knock jokes, but of course, I had a whole book of them. So anyway.

EL: Oh, they're great. And especially when a child tells you one.

KK: That’s right. That’s what they’re there for.

MB: The best is when you have a child who hasn't heard the knock-knock joke you’ve heard 10 million times, and you get to be the person to share the groan-inducing pun with the child. I mean, that's how I imagine Schwartz going to Montevideo and explaining distribution theory, like the experience of sharing this pun and having them go “Ohhh” and slapping their forehead. There's this cultural resonance, to introduce something that you immediately grasp. And yeah, that's a really special experience.

KK: Yeah.

EL: So at the end of the show, we like to invite our guests to plug things, and I'll actually plug a couple of your things because we've sort of mentioned them already. You had a really nice article in Nature. I don't remember, it was a couple years ago—

MB: 2018.

EL: —about this history of the Fields Medal, focusing on Olga Ladyzhenskaya, who was on the short list in ’58 and would have been the first woman to get the Fields Medal if she had gotten it, but it was really interesting because it touches on these things about how the Fields Medal became what it is thought of now and how they made that decision at that time. So go read that. And you also have an article about this distribution stuff that I am completely now blanking on the title of, but it has the word “wordplay” in it, and you probably know the title.

MB: There’s “Integration by Parts” as the title.

EL: Okay.

MB: And then there's a long subtitle. So this is the thing any historian does, is they have some kind of punny title and then this long subtitle. I think one of the reasons I empathize with the theory of distributions is, like, this is how I think as a historian. I come up with a pun, and then I work out how all of the things connect together afterwards. You see that in all of my titles, basically, and papers, That's not that's on my website, mbarany.com, and the show notes.

EL: Yeah, we'll put those in the show notes. We'll link to your website and Twitter in the show notes. And yeah, anything else you want to mention?

MB: Yeah, so if you want all of this math and sociology and politics and stuff about academia and the values of mathematics, then my main Twitter account at @mbarany is the one to follow. If you just want sort of parodies and irreverent observations about math history, then @mathhistfacts is my parody account that I started in August, but the key to that is that behind every thing that looks like it's just a silly joke is actually something quite subtle about historical interpretation. And I always leave that as an exercise to the reader. But I do try to—this was my response to, you know, St. Andrews has this MacTutor archive of biographies of mathematicians that has hundreds and hundreds of mathematicians, these sort of capsule biographies. And they have these little examples, or these little summaries, like so-and-so died on this day and contributed to this theory, and it’s just kind of morbid to celebrate them for when they died. But then even the one that makes the rounds every year on Galileo's birthday, so Galileo is actually one of the—not Galileo, Galois. Galois is one of the few people who actually has an interesting death date, whose death is historically significant, and there's a Twitter account that tweets based on on these little biographical snippets, and does it for his birthday rather than his death day and then says, like, “Galois made fundamental contributions to Galois theory.” So this was my response to that account, those tweeting from these biographical snippets saying there's there's more to history than just when people died and what theory named after them they contributed to, and tried to do something a bit more creative with that.

EL: Yeah, that is fun. I felt slightly personally attacked because I did just publish a math calendar that has a bunch of mathematician’s birthdays on it, but I did choose to only do like a page about a mathematician on their birthday rather than their death day because it just seemed a lot less morbid.

MB: Very sensible. There are some mathematicians with interesting death days. So Galois, Cardano. Cardano used mathematics to predict his death day, so it's speculated that he also used some poison to make sure he got his answer right.

EL: Yikes! That’s a bit rough.

MB: But yeah, there are a few mathematically interesting death days. But yeah, I mean, birthdays are okay, I guess. I'm not super into mathematical birthdays anyway, but better than death days.

EL: Yeah. I mean, when you make a calendar, you've got to put it on some day. And it's weird to put it on not-their-birthday. But yeah, that's a fun account. So yeah, this was great. Thanks for joining us, Michael.

MB: Thanks. This was super fun.

On this episode of My Favorite Theorem, we were happy to talk with University of Edinburgh math historian Michael Barany. He told us about his favorite definition in mathematics: distributions. Here are some links you might find interesting.

Barany’s website and Twitter account
His article “Integration by Parts: Wordplay, Abuses of Language, and Modern Mathematical Theory on the Move” about the notion of the distribution

His Nature article about the history of the Fields Medal
Distributions in mathematics

The Dirac delta function (er, distribution?)

The Danish national team profile page of mathematician and footballer Harald Bohr

Episode 59 - Daniel Litt

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast and so much more. I'm Kevin Knudson, professor of mathematics at the University of Florida. Here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a math and science writer in Salt Lake City, Utah. I have left the county two times since this all happened. We don't have a car, so when I leave my home, it is either on feet or bicycle, which is your feet moving in a different way. But I have biked out of our county now into two different other counties. So it's very exciting.

KK: Fantastic. Well, I do have a car. I bought gas yesterday for the first time since May 26, I think. And yesterday was June 30.

EL: Yes.

KK: And I've gotten two haircuts, but it looks like you've gotten none.

EL: Yes. That’s correct. I’m probably the shaggiest. I've been in a while. My I normally this time of year is buzzcut city, which I do at home anyway. But I don't know.

KK: I will say I’m letting it get a little longer actually. I know I said I got a haircut, but you know, Ellen likes it longer somehow. So here we go. This is where we are. My son's been home for three months, and we haven't killed each other. It's all right.

EL: Great. Yeah, everything's doing as well as can be expected, I suppose. If you're listening to this in the future, and somehow, everything is under control by the time we publish this, which seems unlikely, we are recording this during the 2020 COVID-19 pandemic, right, which—I guess it still stays COVID-19 even though it's 2020 now, to represent the way time has not moved forward.

KK: Right. Time has no meaning. And you know, Florida now is of course becoming a real hotspot, and cases are spiking. And I'm just staying home and, and I have four brands of gin, so I'm okay.

EL: Yeah. Anyway!

KK: Anyway, let's talk math. So we're pleased today to welcome Daniel Litt. Daniel, would you please introduce yourself?

Daniel Litt: Hey, thank you so much. It's really nice to be here. I'm Daniel Litt. I'm an assistant professor at the University of Georgia in Athens, Georgia, likewise, a COVID-19 hotspot. I also have not gotten gas, but I think I've beat your record, Kevin. I haven't gotten gas since the pandemic began.

KK: Wow. That’s pretty remarkable.

DL: I’ve driven, maybe the farthest away I've driven from home is about a 15-minute drive, but those are few and far between.

KK: Sure.

DL: So yeah, I'm really excited to be here and talk about math with both of you.

KK: Cool. All right. So I mean, this podcast is—actually, let’s talk about you first. So you just moved to Athens, correct?

DL: I started a year ago.

KK: A year ago, okay. But you just bought your house.

DL: That’s right. Yeah. So I actually live in northeast Atlanta, because my wife works at the CDC, which is a pretty cool place to work right now.

KK: Oh!

EL: Oh wow.

KK: All right. Is she an epidemiologist?

DL: She does evaluation science, so at least part of what she was doing was seeing how the CDC’s interventions and deployers, how effective they were being help them to understand that.

KK: Very cool. Well, now it would be an interesting time to work there. I'm sure it's always interesting, but especially now. Yeah. All right. Cool. All right. So this podcast is called my favorite theorem. And you've told us what it is, but we can't wait for you to tell our listeners. So what is your favorite theorem?

DL: Yeah, so my favorite theorem is Dirichlet’s theorem on primes in arithmetic progressions. So maybe let me explain what that says.

KK: Please do.

EL: Yes, that would be great.

DL: Yeah. So a prime number is a positive integer, like 1, 2, 3, 4, etc, which is only divisible by one and by itself. So 2 is a prime, 3 is a prime, 5 is a prime, 7, 11, etc. Twelve is not a prime because it's 3 times 4. And part of what Dirichlet’s theorem on primes in arithmetic progressions tries to answer, part of the question it answered, is how are primes distributed? So there is a general principle of mathematics that says that if you have a bunch of objects, they're usually distributed in as random a way as possible. And Dirichlet’s theorem is one way of capturing that for primes. So it says if you look at an arithmetic progressions—that’s, like 2, 5, 8, 11, 14, etc. So there I started at 2 and I increased by 3 every time. Another example would be 3, 6,9, 12, 15, etc—there I started at 3 and increased by 3 every time. So Dirichlet’s theorem says that if you have one of those arithmetic progressions, and it's possible for infinitely many primes to show up in it, then they do. So let me give you an example. So for 3, 6, 9, 12, etc, all of those numbers are divisible by 3. So it's only possible for one prime to show up there, namely 3.

EL: Right.

DL: But if you have an arithmetic progression, so a bunch of numbers which differ by all the same amount, and they're not all divisible by some single number, then Dirichlet’s theorem tells you that there are infinitely many primes in that sequence. So for example, in the sequence 2, 5, 8, 11, etc, there are infinitely many primes, 5 and 11 being the first two [editor’s note: the first primes after 2. But it’s just odd for an even number to be prime]. And it tells you something about the distribution of those primes, which maybe I won't get into, but just their bare existence is really an amazing theorem and incredible feat of mathematics.

EL: So this theorem, I guess, for some of our listeners, and for me, it probably sort of reminds them in some ways of like twin primes or something, these other questions about distributions of primes. Of course, twin primes, you don't need a whole arithmetic progression, you just need two of them. That would be primes that are separated by two, which other than 2 and 3 is the smallest gap that primes can have. And, of course, twin primes is not solved yet.

DL: Yeah, we don’t know that there are infinitely many.

EL: Yeah, people think there are but you know, who knows? We might have found the last one already. I guess that's unlikely. But Dirichlet was proved a long time ago. So can you give me a sense for why this is a lot easier than twin primes?

DL: Yeah, so part of the reason, I think, is that twin primes are much sparser than primes in any given arithmetic progression. So just to give you an example, if you have a bunch of numbers, one way of measuring how big they are is you could take the sum of 1 over those numbers. So for example, the sum of 1/n, where n ranges over all positive integers, diverges; that sum goes to infinity. And the same is actually true for the primes in any fixed arithmetic progression. So if you take all the primes in the sequence 2, 5, 8, 11, etc, and take the sum of one over them, that goes to infinity, since there's a lot of them. On the other hand, we know that if you do the same thing for twin primes, that sum converges to a finite number. And that number is pretty small, actually. We know, up to quite a lot of accuracy, what it looks like. And that already tells you that they're sort of hard to find. And if you have things that are hard to find, it's going to be harder to show that there are infinitely many of them. I mention this sum of reciprocals point of view because it's actually crucial to the way Dirichlet’s theorem is proven. So when you prove Dirichlet’s theorem, it's one of the these really amazing examples where you have a theorem that's about pure algebra. And you end up proving it using analysis. So in this case, the theory of Dirichlet L-functions. And understanding that sum of reciprocals is kind of key to understanding the analytic behavior of some of these L-functions, or at least it’s very closely related.

KK: So I didn't know that result about the reciprocals of the twin primes converging. So even though we don't know that there are infinitely many, somehow…

DL: Yeah, in fact, if there are finitely many then definitely that sum would converge, right?

KK: Yeah, right. That’s—and we even know an estimate of what the answer is? Okay. That’s fascinating.

DL: Yeah, and what you have to do to prove that is show that these primes are sufficiently sparse. And then and then you win. EL: So once again, I am super not a number theorist. So I'm just going to bumble my way in here. But to me, if I'm trying to show that something diverges, I show that it's sort of like 1/n, and if it converges, it's sort of like 1/n2 or, or worse, or better, or however, you want to morally rank these things. So I guess I could imagine it not being that hard to show that twin primes are sort of bounded by n2, or you're like bounded by 1/n2 squared, the reciprocals of that, would that be a way to do this? Or am I totally off?

DL: It’s something like that. You want to show they're very spread out. Yeah, with primes, I do want to mention, so you mentioned like you want to say something like between 1/n or 1/n2. So primes are much, much rarer than integers, right? So it's really somewhere between those two.

EL: Yeah.

DL: So for example, understanding the growth rate of those numbers—the growth rate of the primes and the growth rate of the primes in a given arithmetic progression—is pretty hard. Like that's the prime number theorem, it’s one of the biggest accomplishments of 19th-century mathematics.

KK: Right. Does that help you prove that, though? Maybe it does, right? Maybe not?

DL: Yeah, so proving that the sum of the reciprocals of the primes diverges is much, much easier than the prime number theorem. And as you can prove that in, like, a page or page and a half or something. But it's very closely related to the key input of the prime number theorem, which is that the Riemann zeta function, the subject of the Riemann hypothesis, has a pole at s=1.

KK: All right. Okay. So what's so compelling about this theorem for you?

DL: Yeah, so what I love about it is that it's maybe one of the earliest places, aside from the prime number theorem itself, where you see some really deep interactions between algebra and complex analysis. So the tools you bring in are these Dirichlet L-functions, which are kind of generalizations of the Riemann zeta function. And they're really mysterious and awesome objects. But for me, what I find really exciting about it is that it's like the classic oldie. And people have been kind of remaking it over and over again for the last, like, century. So there's now tons of different versions of the Dirichlet theorem on primes in arithmetic progressions in all kinds of different settings. So here's an example. In geometry, you have a Riemannian manifold, which is kind of a manifold with a notion of distance on it. There's a version of Dirichlet’s theorem for loops in a Riemannian manifold, the first cases of which are maybe do that Peter Sarnak in his thesis. There are versions for over function fields. So I'm not going to be precise about what that means, but if you have some kind of geometric object that's kind of like the integers, you can understand it well and understand the behavior of primes and that kind of object, and how they behave in something analogous to an arithmetic progression. There's something called the Chebotarev density theorem, which tells you if you have a polynomial, and you take the remainder of that polynomial when you divide by a prime, how does its factorization behave as you vary the prime? So there's all kinds of versions of it, and it's a really exciting and cool sort of theme in mathematics.

EL: So kind of getting back to the the more tangible number theory thing—which I guess it's kind of funny that we think of numbers as more tangible when they're sort of the first example of an incredibly abstract concept. But anyway, we'll pretend numbers are tangible. So how does this relate, I remember, and I don't even remember now, I must have been writing some article that related to this, but looking at your primes that are your 1 more than a multiple of 6 versus 1 less and looking at whether there are more or fewer of these. So these are two different arithmetic progressions. The one that's like, you know, 7, 13, let's see if I can add by 6, 19, this, that progression, versus the 5, 11, etc, progression. So is this related to looking at whether there are more of the ones that are one more one less or things like that?

DL: For sure.

EL: I feel like there are all these interesting results about these biases and the distributions.

DL: Yeah, so people call this prime number races.

EL: Yeah.

DL: So what you might do is you might take two different arithmetic progressions and ask are there more prime numbers, like, less than a billion, say, in one of those progressions as opposed to the other? And there are actually pretty surprising properties of those races that I think are not totally well understood. So like even even this recent work of Kannan Soundararajan and Robert Lemke Oliver on this kind of thing.

EL: Oh, yeah, that’s what I was writing about!

DL: Which, yeah, shows some sort of surprising biases. And so that's the reason people think those are cool, is exactly this principle I mentioned before, this general principle of math that things should be as random as they can be. And there are maybe some ways in which our random models of the primes are not always totally accurate. And so understanding the ways in which they're inaccurate and how to fix that inaccuracy, like how to come up with a better model of the primes, is a really big part of modern number theory.

EL: But I guess, the Dirichlet theorem is what you need before you start looking at any of these other things, is you need to know that you can even look at these sequences.

DL: Right. Exactly. Yeah. I mean, how do you study the statistics of a sequence you don't know is infinite? Yeah.

EL: Right.

DL: One thing I’ll mentioned, one cool thing about it is it lets you—it’s not just an abstract existence result. Like, sometimes you just need a prime which is, like, 7 mod 23 to do some mathematical computation. Okay, and if it's 7 mod 23, then it's pretty easy to find one. You can take 7. But if you need a prime, that's a mod b, its remainder upon division by b is a, it's sort of hard to make one in general. And the fact that Dirichlet’s theorem gives them to you is actually really useful. So at least for a mathematician who cares about primes, it's something that just comes up a lot in daily life.

KK: But it's not constructive, though.

DL: Yeah, that's, that's right. It does kind of guarantee that there will be one less than some explicit constant, so in some sense, it's constructive, but it doesn’t, like, hand one to you.

EL: But still, I guess a lot of the time, you probably don't actually need a particular one. You just kind of need to know that there is one.

DL: Yeah.

EL: And where did you first encounter this theorem?

DL: I guess it was, I was probably reading Apostol’s number theory book when I was in college. But I think for me, I didn't really grok it until some other more modern version of it, like one of these remakes showed up for me in my own work. So I wanted to make a certain construction of algebraic curves. So that's some kind of geometric objects defined by some polynomial equations, which have some special properties. And it turned out that for me, the easiest way to do that was to use some version of Dirichlet’s theorem in some kind of geometric context.

KK: Very cool.

DL: So that was really exciting.

KK: Yeah. Well, it's it's nice when, like you say, when the oldies come up on your jukebox. They're useful.

DL: Yeah, exactly.

KK: So another fun thing about this podcast is that we ask our guests to pair their theorem with something. And I mean, I think Evelyn and I are just dying to know what pairs well with Dirichlet’s theorem on primes in arithmetic progressions.

DL: So for me, it's the Arthur Conan Doyle stories about Sherlock Holmes.

KK: Okay.

DL: For a couple different reasons. So first of all, because he's all about making connections between these sort of seemingly unrelated things, just like Dirichlet’s theorem is about making connections between, somehow for the proof, it's about connecting these things in algebra, primes, to things in complex analysis, these L-functions, but then also because it's an oldie that's been remade over and over again. It's still constantly being remade, like with the new BBC Sherlock show.

KK: It’s the best. Yeah, I remember when that was coming out. My wife and I were just so excited every time a new season come out, you know, just “Sherlock! Yes!”

DL: Yeah, just like I'm so excited every time a new version of Dirichlet’s theorem on primes in arithmetic progression comes out.

EL: Yeah, I haven't watched any of the Sherlock TV or movies yet. But we're watching a little more TV these days, and that might be a good one for us to go look at.

KK: It is so good. I mean, the first episode…

EL: Is that the one with Benedict Cumberbatch?

KK: Yeah, but the first one, just, I mean, it just grabs you. You can't not watch it after that. It's really, really well done.

DL: Yeah, they're really fun. Although—oh, go on.

KK: I was going to say the last one, the very last episode, I thought was a bit much.

DL: I don't know that I watched the last season.

KK: Yeah, it was a little…yeah. But you know, still good.

DL: I was reading a couple of the old short stories in preparation for this podcast. Those are also, I highly recommend.

KK: Which ones did you read?

DL: My favorite one that I read recently was, I think it's called the Adventure of the Speckled Band.

KK: Mm hmm.

EL: Oh, yeah.

DL: It's one of the classics.

KK: Right. Yeah. And I think they based one of the episodes on that one, too.

DL: Yeah. that’s right. Yeah.

EL: Yeah, that's a good one. I haven't read all of the Sherlock Holmes it seems like they're practically infinitely many of them. But you know, I had this collection on my Nook and we were moving, so it was like light, and I could read it in the hotel room easily and stuff. And as we were moving to Utah, I think the very first Sherlock Holmes one is set in Utah, or like part of it is set in Utah.

DL: Yeah, maybe the Sign of Four?

EL: Yes, I think it’s the Sign of Four.

DL: Yeah, I think it's one of the first two novellas. So I’ve read every single Sherlock Holmes when I was when I was in high school or something.

EL: Okay. But I was just like, of all things. I didn't know, I hadn't ever read any Sherlock Holmes before. And, like, this British guy writing about this British detective, and it’s set in the state I’m about to move to. It just seemed incredibly improbable to me.

DL: Yeah, I guess he had some kind of fascination with the U.S. because there's that one, which is sort of set in Utah as it was being settled, I guess.

EL: Yeah.

DL: And then there's the case of the five orange pips or something, which actually in a timely way crucially involves the KKK. And so yeah, so there's a lot of sort of interesting interactions with American history.

EL: Yeah, I don't I don't remember if I've read the orange pips.

KK: That figures in the TV series too.

EL: Okay. Yeah, I kind of forgot about those. Those might be a fun thing to go back to, since unlike you, I have not read all of them, and there always seem to be more that I could kind of dive into. I think I kind of tried to read too many at one time, and I just got fed up with what a jerk he is. Self righteous, smug guy.

DL: Yeah, definitely.

EL: Which doesn't make it not entertaining.

DL: If you like this stuff, there's a nother thing I was thinking of pairing. pairing with the theorem. There's a novel by Michael Chabon about a sort of very elderly Sherlock Holmes. Which I don't quite remember the name but part of it is about, you know, what it's like to be Sherlock Holmes when you're 90 and all your friends have left you, and so maybe that might, might appeal to you if you find him sort of an annoying character.

EL: Yeah. Could that be the Yiddish Policeman's Union?

DL: I don't think so. It's a much shorter book.

EL: Okay. That’s the title I could remember.

DL: That one is also excellent. It just doesn't have Sherlock Holmes in it. [Editor’s note: the book is The Final Solution: A Story of Detection.]

EL: Okay. Well, when you were talking earlier about the theorem, you used the word, I think you used the word remake or sequel or something. So I was wondering if you were going to pick movies, or something like that for your pairing. But this kind of works, too, because each one, it’s not a not remakes exactly—I guess with the movies there are remakes, movies and TV shows. But the stories are all, like, some new sequel. Like, here's a slightly different adventure that Sherlock goes on. And slightly different clues that he finds.

DL: Yeah, exactly. That's one thing that I love about math in general is that so much of it is you look at something classic, and then you put a little spin on it. Like I do a little exercise with some of the grad students at UGA in one of our seminars where we take a classic theorem. I think most recently, we did Maschke’s theorem, which is something about representation theory. And then you highlight every word in the theorem that you could change, and then kind of come up with conjectures based on changing some of those words, or questions based on changing some of those words. That's a really fun exercise in, kind of, mathematical remakes.

EL: That does sound fun. And I mean, I think that's one of the things that you learn, especially in grad school, is just how to start looking at statements of theorems and stuff and seeing where might there be some wiggle room here? Or where could I sub out a different space or a different set of assumptions about a function or something and get something new.

DL: Right, exactly. Yeah, definitely. With Dirichlet’s theorem, that happens so many times.

EL: Yeah, well, that's very fun. Thanks for bringing that one up. Thinking about it, I’m a little surprised that we haven't had it already on the podcast.

DL: Yeah, it's classic.

EL: Yeah, it really is.

KK: So we also like to give our guests a chance to plug anything that they're working on. You're very on Twitter.

DL: Yeah, that's right. You can you can follow me @littmath.

KK: Okay.

DL: So what do I want to plug? I think aside from Sherlock Holmes, who maybe needs no plugging, first of all, I would like to plug the Ava DuVernay documentary 13th, which I really liked and I think everyone should should watch.

EL: Yeah, and I saw that's free on YouTube right now. I don't know if that's temporarily, but I’m not a Netflix subscriber.

DL: Yeah, it is on Netflix. And yeah, I don't know if it'll be available on YouTube but for free by the time this comes out, but probably a nominal cost. In terms of things I've done that I think people who listen to this podcast might like, I did a Numberphile video about a year ago on the on it one of Hilbert’s problems about cutting up polyhedra and rearranging them that someone might someone who likes this podcast might enjoy. So if you google “Numberphile the Dehn invariant,” that’ll come up.

EL: Oh, great.

KK: Cool. All right.

EL: We’ll put links to those in the show notes. Yeah.

KK: All right. Well, thanks for joining us.

DL: Thank you guys so much for having me. This was a lot of fun.

KK: I learned something. I learn something every time, but I'm always surprised at what I'm going to learn. So this is this has been great. All right. Thanks, Daniel.

DL: All right. Thank you so much.

On this episode of My Favorite Theorem, we were happy to get to talk to Daniel Litt of the University of Georgia about Dirichlet's theorem on primes in arithmetic progressions. Here are some links you might find useful as you listen:

Litt's website
Litt's Twitter profile
More about the Dirichlet theorem from Wikipedia
Tom Apostol's number theory book
The article Evelyn wrote about surprising biases in the distributions of last digits of prime numbers
Michael Chabon's novella The Final Solution: A Story of Detection
Litt's Numberphile video about the Dehn invariant
Ava DuVernay's documentary 13th

Episode 58 - Susan D'Agostino

Kevin Knudson: Welcome to My Favorite Theorem, a podcast about math and so much more. I'm one of your hosts, Kevin Knudson, professor of mathematics at University of Florida. And here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a math and science writer in Salt Lake City, Utah. So how are you, Kevin?

KK: I’m fine. It's it's stay at home time. You know, my wife and son are here and we're sheltered against the coronavirus, and we've not really had any fights or anything. It's been okay.

EL: That’s great!

KK: Yeah, we're pretty good at ignoring each other. So that's pretty good. How about you guys?

EL: Yeah, an essential skill. Oh, things are good. I was just texting with a friend today about how to do an Easter egg hunt for a cat. So I think everyone is staying, you know, really mentally alert right now.

KK: Yeah.

EL: She’s thinking about putting bonito flakes in the little eggs and putting them out in the yard.

KK: That’s a brilliant idea. I mean, we were walking the dog earlier, and I was lamenting how I just sort of feel like I'm drifting and not doing anything. But then, you know, I've cooked a lot, and I'm still working. It's just sort of weird. You know, it's just very.

EL: Yeah, time has no meaning.

KK: Yeah, it's it's been March for weeks, at least. I saw something on Twitter, Somebody said, “How is tomorrow finally March 30,000th?”

EL: Yeah.

KK: That’s exactly what it feels like. Anyway, today, we are pleased to welcome Susan D'Agostino to our show. Susan, why don't you introduce yourself?

Susan D’Agostino: Hi. Thanks so much for having me. I really appreciate being here. I’m a great fan of your show. So yeah, I'm Susan D’Agostino. I'm a writer and a mathematician. I have a forthcoming book, How to Free Your Inner Mathematician, which is coming out from Oxford University Press. Actually, it was just released in the UK last week and the US release will be in late May. And otherwise, I write for publications like Quanta, Scientific American, Financial Times, and others. And I'm currently working on an MA in science writing at Johns Hopkins University.

KK: Yeah, that's pretty cool. In fact, I pre-ordered your book. During the Joint Meetings, I think you tweeted out a discount code. So I took advantage of that.

SD: Yes. And actually, that discount code is still in effect, and it's on my website, which I'll mention later.

EL: Great. So you said you're at Hopkins, but you actually live in New Hampshire?

SD: Exactly. Yes. I'm just pursuing the program part-time, and it's a low-residency program. So I’m a full-time writer, and then just one class a semester. It creates community, and it's a great way to meet other mathematicians and scientists who are interested in writing about the subject for the general public.

EL: Nice. I went to Maine for the first time when I was living in Providence last semester and drove through New Hampshire, which I don't think is actually my first time in New Hampshire, but might have been. We did stop at one of the liquor stores there off the highway, which seems like a big thing in New Hampshire because I guess they don't have sales tax.

SD: No sales tax, no income tax, “Live Free or Die.” Yeah, and you probably test right around where I live because I live in New Hampshire has a very short seacoast, about 18 miles, depending on how you measure it. We live right on the seacoast.

EL: Oh yeah, we did pass right there. Wonderful. Yeah, the coast is very beautiful out there.

SD: I love it. Absolutely love it. I'm feeling very lucky because there's lots of room to oo outside these days. So, yeah, just taking walks every day.

EL: Wonderful.

KK: So you used to be a math professor, correct?

SD: Yes.

KK: And you just decided that wasn't for you anymore?

SD: Yeah, well, you know, life is short. There's a lot to do. And I love teaching. I had tenure and everything. And I did it for a decade. And then I thought, “You know, if I don't write the books I have in mind soon, then maybe they won't get done.” I've got my first one out already, only two years into this career pivot to writing, and I’m working on my next one. And I always had in mind, in fact, I have a PhD, but I also have an MFA. So I have a terminal degrees both in math and writing. And I always had one foot in the math world and one foot in the writing world, and I realized I didn't want to only live in one. So this is my effort to live fully in both worlds.

KK: That’s awesome.

EL: Yeah. Nice. So the big question we have now of course, is what is your favorite theorem?

SD: Okay, great. My favorite theorem is the Jordan curve theorem.

KK: Nice.

SD: Yeah. It’s a statement about simple closed curves in a 2-d space. So before I talk about what the Jordan curve theorem is, let's just make sure we're abundantly clear about what a simple closed curve is.

EL: Yes.

SD: So, a curve—you can think about it as just a line you might draw on a piece of paper. It has a start point, it has an end point. It could be straight, it could be bent, it could be wiggly, it could intersect itself or not. The starting point and the end point may be different or not. And because this is audio, I thought maybe we could think about capital letters in a very simple font like Helvetica, or Arial. So for example, the capital letter O is a is a curve. When you draw it, it has a start point and an end point that are the same. The capital letter C is also a curve. That one has a different starting and end point, but that's okay. It satisfies our definition. Capital letter P also. That one intersects itself in the middle, but it's still it's a curve.

Okay, so a simple curve is a curve that doesn't intersect itself along the way. It may or may not have the same starting and end point, but it won't intersect itself along the way. So capital letter O and capital letter C are both simple. But for example, the capital letter B is not simple, because if you were to start at the bottom, go up in a vertical line, draw that first upper loop and then the second upper loop, between the first and second upper bubbles of the B, you will hit that initial vertical line that you drew. So it's not simple because it touches itself along the way.

And a closed curve is a curve that starts and ends at the same point. So the letter O is closed, but the letter C is not because that one starts in one place ends in another.

KK: Right.

SD: Moving forward as we talk about the Jordan curve theorem, let's just keep in mind two great examples of simple closed curves: the letter O, and even the capital letter D. It's fine that that D has some angles, in the bottom left and upper left. So corners are fine, but it needs to start and end in the same place and doesn't intersect itself other than where it starts and ends.

Okay, so the Jordan curves theorem tells us that every simple closed curve in the plane separates the plane into an inside and an outside. So a plane, you might just think of as a piece of paper, you know, an 8 1/2 by 11 piece of paper, let's draw the letter O on it. And when you draw that letter O, you are separating that piece of paper, the surface, into a region that you might call inside the letter O and another region that you might call outside the letter O. And the second part of the Jordan curve theorem tells you that the boundary between this inside and that outside formed by this letter O is actually the curve itself. So if you're standing inside the O, and you want to get to the outside of the O, you've got across that letter O, which is the curve.

Okay, so that doesn’t sound very profound.

KK: It’s obvious. It’s just completely obvious.

EL: Any of us who are big doodlers—like, when I was a kid, at church, I was always doodling inside the letters in the church bulletin. That’s the thing. I know that there's an inside and outside to the letter O.

SD: You do. Yes. And you could ask your kid brother, kid, sister, whoever. Anyone—you probably didn't need a big mathematical theorem to assure you of this somewhat obvious statement when it comes to the letter O. Okay, so, I do want to tell you why I think it's really interesting beyond this fact that it seems obvious. But before I do, I just want to make two quick notes. And one is that you really do need the simple part, and you really do need the closed part of the theorem because, for example, if you think about a non-closed curve, like the letter C, and you're standing on the piece of paper around that letter C, maybe even inside, like where the C is surrounding you, it actually doesn't separate the piece of paper into an inside and an outside. And then you also need the non-simple part because if you think about the letter P, which is not simple because it intersects itself, if you think about the segment of the P that's not the loop, so the vertical bottom part of that P, that is part of the curve, the letter P, and that piece of the curve doesn't separate—so even though that P seems to have a little bit of a bubble up there, in the in the loop of the P, the bottom part of the P is part of the curve, and it's not the boundary between the inside, what you might consider the inside of the P, and the outside of the P. So you really do need the simple part and the closed part.

KK: Right, right.

SD: Okay, so the reason I think it's interesting, in spite of the fact that it seems obvious, is because it actually isn't very obvious. And it's not obvious when you talk about what mathematicians love to call pathological curves.

KK: Yeah. Okay. No, I know, I know, the theorem I just wanted to shrug my shoulders and say, “Oh, look, it's just a special case of Alexander duality.” Right? And so surely it works. But yeah, okay.

SD: And there are other poorly-behaved curves, or misbehaved curves, like another curve you might think about is the Koch snowflake. So one way of thinking about the Koch snowflake is—again, I'm going to wave my hands a little bit here because we're in audio and I can't draw you a picture—but if you think about the outline of a snowflake, and there's a prescribed way to draw the Koch snowflake, but I'm going to simplify it a little bit. Imagine the outline of a snowflake, so not the inside or the outside of the snowflake, just the outline of it. And on a Koch snowflake, that snowflake is going to have jagged edges. It's going to zig and zag as it goes along the outline of the snowflake. The Koch snowflake actually has an infinitely jagged curve, line, to draw it. So it's not that it has 1000 zigs and zags or 1 million or even 1 billion. It has an infinite number of zigs and zags going back and forth. So you know, it's a little bit easier to imagine the— what could loosely be defined as the inside of the Koch snowflake, and the outside of the Koch snowflake when you imagine one being drawn on a piece of paper. You know, right in the heart of the very dead center of that Koch snowflake, you could probably feel pretty confident saying, “Hey, I'm inside the Koch snowflake.” And then far outside, you could be confident saying, “I'm outside of the snowflake.” But if you think about yourself right up against the edge of this Koch snowflake. And put yourself right there. Then as you think about this boundary of the Koch snowflake, the boundary is supposed to be what separates the inside from the outside, but if you're right up close to that boundary, and in the process of drawing an infinite number of constructions to get the ultimate Koch snowflake. You continue zigging and zagging, you add more zigs and zags every time. Then even in the steps that it takes you to get to your drawing of the Koch snowflake, at some point, it might seem like “Hey, I'm inside. Oh wait, now they zigged and zagged and I’m outside. Oh, wait, they zigged and zagged some more. Now I'm inside again.” So it seems like even in the finite steps that you need to take to draw that Koch snowflake, to imagine what the it is in its infinite world, it seems like that boundary is not really clear. So again, another place where it makes you stop and say, “Wait a minute, maybe the Jordan curve theorem is not as obvious as it first looked.”

KK: Right. Why do you love this theorem so much?

SD: Yeah, so I love it. It actually it kind of goes along with your question of what do you pair it well with? So maybe I'll just jump ahead to what's sugar. Yeah. So, um, because even in my book and in the chapter that in which I discuss the Jordan curve theorem, I actually paired it with a poem. And the poem is by a New Hampshire native, Robert Frost, who actually went to Dartmouth, which is where I got my doctorate. And one of my favorite poems by Frost is called “The Road Not Taken.” And in the beginning of the poem, he's standing in front of this fork in the road, essentially, and he's looking at both options, realizing, “Okay, I've got to go left or I've got to go right.” You know, he starts off:

Two roads diverged in a yellow wood, And sorry I could not travel both And be one traveler, long I stood And looked down one as far as I could To where it bent in the undergrowth;

So he's standing here and he's saying, “Well, which path should I take?” And he notices one that he calls you know, “it was grassy and wanted wear” and had no leaves—what was what was the line—“in leaves no step had trodden black.” And he ultimately comes to the conclusion that he's going to take the past path less traveled. You know, at the very end of the poem, he says, “Two roads diverged in a wood and I—/ I took the one less traveled by,/ And that has made all the difference.” And it strikes me that what Frost is telling us, and what the Jordan curve theorem is telling us, is take the paths that are more unusual, that aren't well trodden, that people don't always look at first, that aren't as obvious or as paved for us. Maybe it's a path that's going to make you question whether you're inside or outside. Or maybe it’s going to have what feels like this amorphous boundary that you can't quite put your finger on. I guess it reminds me that sometimes making a non-traditional choice in life, or looking at pathological objects in math, is actually something very engaging to do, and can can make a life a little bit more interesting.

You know, when I first heard about this theorem, I had the same reaction that most everybody else does: Okay, so I can just draw a curve—you know, you say a curve and you think, “Oh, I can just draw a curve.” I'm just going to do a squiggle on a piece of paper. And as long as I make it simple and closed, then it might be the letter O or it might be some blob that doesn't intersect, but at least starts and ends where it ends where it started. You know, I remember thinking, wait, why does this theorem get its own name? Why isn’t it just lemma 113.7?

EL: An observation.

KK: Clearly.

SD: Why did it get its own name? A I remember asking, and a lot of people, at first everybody was happy to recite the theorem and and say what it was and laugh at how obvious it was, but then later, I kept searching and searching, and then finally I ended up discovering that in fact, it wasn't as obvious, but in order to appreciate how it’s not that obvious, you needed to look at the paths not taken, the more unusual lines and curves.

EL: Yeah, so this is a theorem that, of course, I I feel like I've known for a long time, not just in the “it's obvious” sense, but in the sense that it's been stated in classes that I took—and feel entirely unconfident about knowing anything about it's proof, at least in the general case. I feel like the the difference between how much I have used it and relied on it and what I actually understand of how to prove it is very large.

SD: Yeah, honestly I can say the same thing. My background is in coding theory, definitely not topology. And honestly, I never saw topology as my strength. It was always something that I was in awe of, but also found extremely challenging or less intuitive to me. But I had looked at the proof long ago. I haven't looked at them deeply recently. There are a number of different approaches. But yeah, I feel the same, that even—the statement sounds simple and it's not, and to my understanding, the proofs are also non trivial.

KK: Yeah. I mean, I was sort of being glib earlier and saying it's just a special case of Alexander duality, like that's easy to prove.

EL: Yeah. Right.

KK: I mean, I was teaching topology this this semester, and I was proving Poincaré duality, which is a similar sort of thing, and it's highly non-trivial. I mean, you break it into a bunch of steps, and it sort of magically pops out of it. And I think that's kind of the case here. It's like, you break it into enough discrete steps where each thing seems okay. But in the end, it is a lot of heavy machinery. And like even for Poincaré duality, in the end you use Zorn’s lemma I mean, there's some kind of choice going on. I think when when Jordan—actually, did Jordan even state this theorem? Or is this one of those things where where Jordan gets the credit, but it wasn't really him?

SD: Actually, I don’t know, and now I need to know that answer.

EL: I think he did.

KK: Did he?

EL: Yeah, not to toot my own horn but I’m, gonna anyway, the calendar that I published this year, the page-a-day calendar, still available for purchase, I think Camille Jordan’s birthday is pretty early. It's sometime in January, so I've actually even read this not too long ago. And I think he did publish it and did have a proof of it. And there's an interesting article, I believe by Thomas Hales, about his about Jordan’s proof of the Jordan curve theorem, I guess maybe to some extent defending from the claim some people have that that he never had a rigorous proof of it. I did read that for doing the calendar, but it was over a year ago at this point and I don't quite remember. But yeah, you can find a reference to it on my calendar. I will also include that in the show notes.

KK: And also the same Jordan of Jordan canonical form.

SD: Right.

KK: Pretty serious contributions there from one person.

SD: Absolutely.

KK: Yeah. All right. I actually like this pairing a lot.

EL: Yeah.

KK: And and since you live in New Hampshire, it's perfect.

SD: Yes. I have a number of New Hampshire references in my book because I just feel like I wanted to humanize math to the extent that I could, while still tackling pretty substantial ideas. But any time I had an invitation to bring in something from left field that was actually meaningful to me, I just went for it.

EL: Yeah.

SD: I’m sure Evelyn, too, it sounds like you're up on all of the mathematicians’ birthdays at this point because of your calendar.

EL: I know a few of them now. More than I did two years ago.

SD: Right.

KK: So it was like to give our guests a chance to plug anything. You’ve already plugged your book. Any other places we can find you online?

SD: Yeah, well, lately, I've been writing for Quanta magazine, which has been very exciting. And in fact, I have a few math articles already out this year. And I have a very special one—I can't tell you the topic. I'm not supposed to—it should be coming out April 15. And I'm very excited about that article that I believe is going to be on April 15, assuming everything is fine with the publication schedule, given the pandemic. But yeah, listeners can find links to my articles on my website, which is just susandagostino.com. And you can find information about my books and my articles and what I'm up to there. v KK: Cool. Well, thanks so much for joining us, Susan. This was a good one.

EL: Yeah, lovely to chat.

SD: Great. Well, thank you so much. And you know, I love the show, and really, it was my honor to be here. Thank you.

KK: Thanks.

On this episode of My Favorite Theorem, we talked with mathematician and science writer Susan D'Agostino. Here are some links you might find interesting as you listen.

D'Agostino's website
How to Free Your Inner Mathematician, her new book (find a discount code on her website)
Evelyn's article about the Koch snowflake
Thomas Hales' article about Camille Jordan's proof of the Jordan curve theorem (pdf)

Evelyn's page-a-day math calendar

The article D'Agostino was excited about towards the end of the podcast was this interview with Donald Knuth

Episode 57 - Annalisa Crannell

Evelyn Lamb: Welcome to My Favorite Theorem, joining forces today with Talk Math With Your Friends. I'm Evelyn Lamb. I co-host this podcast. I'm a freelance math and science writer in Salt Lake City, Utah. And this is your other host.

Kevin Knudson: Hi, I'm Kevin Knudson, professor of mathematics at the University of Florida, where it is boiling hot today, and I’m very happy to be in this—how would they put this on on TV?—crossover event, right?

EL: Yeah.

KK: So like, I think last night on NBC, on Wednesday nights, there are all these shows that take place in Chicago: Chicago Med and Chicago PD and Chicago Fire, Chicago Uber, who knows what. Anyway, sometimes they'll just merge them all into one three-hour super show, right? So here we go. This is the math version of this, right?

EL: Yes. And I realized today that our very first episode of My Favorite Theorem, we published that in late July 2017. So this is our early third birthday! And we're so glad that people came to join us! And we are very happy today to have our guest Annalisa Crannell with us. Hi, Annalisa. Can you introduce yourself and tell us a little bit about yourself?

Annalisa Crannell: So hi, my name is Annalisa Crannell. I profess mathematics at Franklin and Marshall College, which is in south-central, southeastern Pennsylvania. It's a small liberal arts college. I got my PhD working in differential equations, partial differential equations, nonlinear differential equations, switched into discrete dynamical systems, topological dynamical systems, but for the past 10 or 15 years have been really thinking hard about projective geometry applied to perspective art.

KK: That’s quite the Odyssey.

AC: Yeah, I was really influenced by by Paul Halmos saying that one of the marks of a really good mathematician is that they can change fields. And so yeah, I feel like I'm trying to enjoy so many different aspects of what this profession allows us to do.

EL: And a fun story, at least it was fun for me, is that one time you were here in Utah giving a talk at BYU, which is down the street. And we went to an art gallery and you pulled out your chopsticks and showed me how you use your chopsticks to help you know where to stand to best appreciate art, and it was just so amazing to me that that was this thing that you could do. So that was that was a lot of fun. And I think it just, to me, sums up the Annalisa experience.

AC: Thank you. Yeah, summing, I guess, is a good thing for mathematicians. I think everybody should carry chopsticks with them. I mean, it's great. It's frugal. It helps you avoid to trash, but it also helps you do really cool mathematics. So what's what's not to love about them?

EL: Yeah. So what is your favorite theorem?

AC: So if you had asked me about five years ago, I would have said the intermediate value theorem. But today, I am going to say no, Desargues’ theorem. So Desargues’ theorem first came into human knowledge in the 1640s. And it's a theorem that sounds like it's sort of about planar geometry, but I really think of it as being about perspective. So is this when I'm supposed to tell you what the theorem says?

KK: Yes, please.

EL: Yeah. Okay, should we all get out our—so this is one, I feel like I always need like a piece of paper. (I’m trying to hold it up, but I’ve got a Zoom background.) But I got my piece of paper out so I can hopefully follow along at home.

AC: Yeah. If you had a piece of paper or a chalkboard right behind you, you could imagine that you would have a triangle, like, standing up on a glass pane. And then on one side of this glass pane would be maybe a magician or somebody holding a light. Maybe your granddaughter drew the magician. (Okay, for people in the podcast, I'm showing a picture that my granddaughter drew on the chalkboard.) If this light shines on the triangle, then it casts a shadow, and the shadow is also a triangle. And so we say those two triangles are perspective from a point, the point is the light source. And we say that because the individual corners, the corresponding corners, are colinear with the light source. So A and the shadow of A are collinear with a light. B and the shadow of B are colinear with a light. But it turns out that those shadows, the triangle and its shadow, are also perspective from a line. And what that means is that if you think not about the points on the triangles, but the three lines on the triangles, and you really think of them as lines, not line segments, so going on forever, then the corresponding lines will also intersect along a line. And you can think of that second line, which we call the axis, as the intersection between the plane of glass that's sitting up in the air and the ground. So the interesting thing to me about Desargues’ theorem is that it pretends like it's a theorem about planar geometry, because this theorem holds when the two triangles are both in the same plane, in R2 or something, but the best ways of proving it, the most standard ways of proving it, are using essentially perspective, going out into three dimensions and proving it for two completely different planes and then pushing them back down into the regular plane. And so to me, this is a really interesting example of sort of how art informs math rather than the other way around. Or maybe they both inform each other.

EL: So going back a little bit, to me when I've I've looked at Desargues’ theorem before, somehow there's this big conceptual leap to me between perspective from a point and perspective from a line. Perspective from a point seems really easy to think about, and perspective from a line, I just have trouble getting it into my brain.

AC: Yeah, I do think perspective from a point is so much more intuitive. And so, so the minorly intuitive, the somewhat intuitive way of thinking of this axis, is you can sort of pretend like it's a hinge. So if these two triangles will sort of fold on to each other from the hinge—the triangle on the glass and the triangle on the ground can fold along this hinge—then they’re perspective from a line. So if you think about something that's in the real world, a flat thing in the real world, and its mirror image, then those two, it's hard to say whether they're perspective from a point, but the lines in the real world thing and the lines in the mirror will intersect along the line where the mirror hits the ground. And so that's that's another way of thinking of this axis, sort of three dimensionally.

KK: So I want to think about this in projective space, which probably isn't correct. Or maybe it is. I don't know. I mean, so these lines are points in projective spaces. This is this, how one might go at this in some other way? I asked the wrong question. I'm sorry.

AC: So that's not exactly the way that I think of it because I think of the line as a line in projective space.

KK: Okay.

AC: And the point is a point in projective space. So the point comes from, you could say, from a one-dimensional line in R-whatever.

KK: Okay.

AC: And so here's one of the interesting things about this theorem and about me loving this theorem. In 2011, one of my coauthors and I wrote a book on the mathematics of perspective art, and we used Euclidean geometry all the way through. We were giving a MathFest mini-course on this and a young mathematician came up to us and said, “I just love how you use projective geometry in art because I learned projective geometry and felt like it had to have something to do with art. And you guys are the ones that explained to me how it does.” And Mark and I turned to each other. We're like, “What kind of geometry?” So neither of us had ever taken a projective geometry class. Neither of us had ever learned any projective geometry. We did not know that it existed. And so this young mathematician ended up changing our lives. We ended up working with her and really learning a bunch of projective geometry in order to come out with our most recent book, which came out last December. And so when you ask questions that get into really deep projective geometry, I'm like, “Ooh, I have to write that one down because that's something else I have to go learn.” So for those of you young mathematicians out there, I just want to say learning new stuff and not knowing stuff is is really so much fun! Don't be afraid of starting something new, even if you don't know it all.

EL: And how did you first encounter Desargues’ theorem?

AC: Oh, man, so I first encountered Desargues’ theorem when, Fumiko Futamura, this young mathematician, had convinced me I needed to learn it. So I bribed an undergraduate to go through Coxeter’s Projective Geometry with me because it seemed like that was the standard book. And Coxeter is, like, the famous guy in this realm, and he is completely non-intuitive. So I found Desargues’ theorem in there, and I'm like, “I have no idea what this means.” The notation is awful. The diagrams are awful. Everything about this is awful. And so I read through his book trying to say, “What does this have to do with art?” And that was a really fun way to read it. So we just decided Desargues’ theorem is about shadows.

EL: Well, I was wondering. So I remember you have also given a talk about squares that kind of blew my mind, where I guess the the thesis of the talk is that all configurations of four points are a square, if you look at it from the right way. Is Desargues’ theorem related to that theorem? I feel like when you said the word shadow that is what reminded me of that other talk.

AC: Yeah, thank you. So that's really cool. So most of us know what the fundamental theorem of calculus says. Most of us know what the fundamental theorem of algebra says. The fundamental theorem of projective geometry in one sense really ought to be Desargues’ theorem. So you can think about these triangles, these points, these lines as objects. For mathematicians, we care about verbs. So a verb is the function. So you can think of a perspective mapping as mapping one set of points and lines to another set of points and lines with this particular rule that says that corresponding points have to line up with the sun, which you call the center, and corresponding lines have to line up with the axis, this hinge. But there's other functions that take points to points and lines to lines. So we know in linear algebra, you can do this all the time, and in linear algebra sets of parallel lines go to other sets of parallel lines. But there's other kinds of functions that do this. They're called colineations. So the fundamental theorem of projective geometry says that if you have four points and their images, and you know that points go to points and lines go to lines, then the entire rest of the function is pre-determined, we know that.

So Desargues’ theorem says that one kind of colineation is perspective mappings, right? Just, like, a shadow or mapping from the floor, this tiled floor onto your canvas through a window. We know from linear algebra, there are these other affine transformations. And so one really cool theorem that I totally love is if you have something that's not a linear algebra one, that's not an affine transformation, then it's automatically a perspective transformation together with an isometry. So you took a photograph and you moved it. That's this notion that every single thing that you do with four points going to four other points that determines a whole function. So yeah, so anytime you have four points connected by four lines, even if they look like a bow tie, or they look like Captain Kirk’s Star Trek logo, it turns out that's actually a weird perspective image of a square moved around somewhere.

EL: And you just have to figure out where you should stand to see it as a square.

AC: Yes, exactly.

KK: Are you guaranteed to be able to—so if it's on the wall, say, could you have to, like, lift it up into a third dimension to be able to see it correctly?

AC: So one of the weird things that happens is if you have a bow tie, we sort of think of a bow tie is that the inside of the bow tie, you would imagine that has to go to the inside of the square. And that is not actually the way it happens. So let's let's think about something that's much more familiar to us. Can you map a circle through perspective into other weird shapes like an ellipse? Well, Sure you can. So imagine that you've got a lampshade, and you've got a circular lampshade, and the shadow that it projects onto the wall is actually a hyperbola. We know that. And the light from the inside of the shadow goes to the part of the hyperbola that goes off towards infinity. Well, if you have the bow tie, think about the area outside of the “x” as almost a hyperbola. So this is when it would be so wonderful if I could actually draw pictures, but it's a podcast. On the on the bow tie, there's two sides that are parallel to each other, and then there's this weird “x” in the middle. The parallel sides, extend them out towards infinity from the bow tie. Right? That turns out to be where the square goes, so if you had a square lampshade, it would cast a shadow that would look like this outside of the bow tie. So the same way that a circular lampshade casts a shadow that looks like the outside of the hyperbola, the U shape of the hyperbola.

KK: My desk lamp is a rectangle, so I’m trying to see if it’s casting the right shadow here.

EL: Yeah, some experiments you can do. I feel like it's this “expand your mind on what a square is” kind of idea.

KK: Got to get rid of those old ideas, man.

EL: Yeah. I know that we we traveled a little bit from Desargues’ theorem and I want to give you a chance to circle back and for me

KK: Or square back. Sorry.

EL: Or square back, or projectively bow tie back to Desargues’ theorem, and I guess what do you love so much about it?

AC: What do I love so much about Desargues’ theorem? One of the things that I love is that it really tightly connects mathematics informing art and art informing mathematics. So Desargues himself, we don't know if he actually wrote this up and published it. We don't have a copy of his original manuscript. We do have something that came out from one of his, sort of acolytes, one of his followers, a guy named Bosse. And if you look at Bosse, okay, to draw Desargues’ diagram, you need 10 points: the three on the first triangle, the three on the second triangle, the sun, that gives you seven, and then the three along the axis. You also need 10 lines: the three on the triangle, the three on the other triangle, the three light rays, that gives you nine, and then the axis. When Bosse first published his diagram, his diagram was incomprehensible. It had 20 lines and 14 points, and it was just really a mess. And it was hard to even figure out where the heck the triangles were.

KK: Yeah, I don’t see them.

AC: And he ended up proving this not using sort of standard geometry, using using numerical stuff called cross-ratios. But the the proofs that make the most sense, that are convincing our proofs that allow us to think about things in three dimensions and use art. So that's one of the cool things, is that actually drawing, if you go and you shade in Bosse’s diagram in a cool artistic way, all of a sudden it sort of pops into 3-d and you can see it, but his original diagram not so much. The same is true of a lot of different proofs. If you try to imagine them as three-dimensional, if you draw them as three-dimensional, the proof becomes more obvious.

But also Desargues’ theorem is actually useful for artists because if you want to draw the shadow of something, if you want to draw the shadow of a kite, if you want to draw a reflection, shadows and reflections, they are projections, so projective geometry, and how do you know how to draw this? You have to use the fact that the shadow or the reflection, or this this projective image, however, you've made it, is perspective from a point and perspective from a line. So you're constantly using Desargues’ theorem to draw these images of images within your image. It just becomes so incredibly useful.

KK: My wife's an artist, but I can't imagine that she would use this. I mean, if you walked up to a typical artist, are they going to say, “Oh yeah, I use Desargues’ theorem all the time?” Or is it just a sort of an intuitive thing where people who are very good at drawing in perspective, can just kind of naturally draw it that way?

AC: Oh, yeah. So the truth is that Desargues’ theorem has really only pretty much been used by mathematicians, and occasionally misused by mathematicians. There's a description in a book by a guy named Dan Pedoe of Desargues’ theorem to draw the image of a pentagon on the top of a square, and he just completely gets it wrong. And Mark and I think that's hilarious. This book has been reproduced zillions of times. Anyway.

So no, actually artists have this incredible skill. One time, we had asked mathematicians and artists at one of our workshops to try to divide the image of a flag into three equal pieces perspectively. So imagine you're drawing the Italian flag going back into the distance, right? How do you do this? In the real world? This there's the three bars are evenly spaced, but in perspective, they're not. And the artists stood up and said, “Well, you just eyeball it, and you just put them here.” And I was horrified. This is not approved. This is not correct. My colleague Mark said, “Okay, this is good. But for those of us who can't just eyeball it, let's see if we can come up with a construction.” And eventually somebody did. They came up with a really cool geometric construction. And Mark had them put this up over the artist’s solution and it was spot on. As a mathematician, I decided to go take an art class. And one of the things we were supposed to do was to draw cans. And so the top of a can is circular, and so the image was going to be an ellipse. And I could not get the proportions right. My ellipses were so awful. So I would say that disarms is an incredibly useful tool for drawing things that look very accurate for people who do not know art, but who are good at math.

KK: Right.

AC: That’s a really long answer to your question. Yeah, artists don't tend to use it, but it really is a useful thing for drawing things that look correct.

KK: Cool. All right.

EL: And you've incorporated this into a class that you teach to help people, I don't know if the purpose of the class is more math or more perspective drawing, but it seems like an interesting mix.

AC: Yeah, we have a course called Perspective and Projective Geometry. We actually have a book that's come out that has Desargues’ theorem right on the cover up there. And it's aimed at the intro to proofs level. So it really teaches students to make conjectures about what they're seeing in the world and then to try to prove those conjectures, but also to try to draw. Ao it's actually sort of an applied course. So they, this students, when we introduce them to Desargues’ theorem, they're actually drawing the shadow of the letter A, and then discovering Desargues’ theorem, and then proving it using many colors and, yeah, lots of cool lines.

It's so much fun! It's a course that really attracts a very unusual swath of students. They all are students who love math, and who are art-curious. Almost none of them are good at art. But I tend to get more women than men in the class. I have often had my class being highly diverse in terms of races and ethnicities. And so for me, it's a fun class. I didn't do it just for the sake of promoting diversity in the math major, but it's sort of unintentionally has done that. And that's a really good feeling.

KK: Very cool. So another thing we like to do on this podcast is ask our guests to pair their theorem with something. So what pairs well with Desargues’ theorem?

AC: Yeah, so I think I already hinted at this, so anything that you can eat with chopsticks goes really well with Desargues’ theorem because chopsticks allow you to have wonderful food and do math at the same time, and what could be better?

KK: So basically, anything you can eat, then, right, you can eat anything with chopsticks?

AC: Soup is a little bit tricky, but yes.

KK: But you drink the soup, right? They give you the chopsticks, you’ve had ramen, right? There's the chopsticks for the noodles.

AC: Yes. Exactly.

EL: Do you have a favorite food to eat with chopsticks?

AC: Oh my goodness. Pretty much everything. I was just realizing ice cream is not so easy with chopsticks.

EL: Yeah.

AC: I think yesterday was national ice cream day. Yeah, I don't I don't know. I take my chopsticks with me in my in my planner bag, and a spoon. And so when I go to restaurants if they try to give me plastic things, I use my chopsticks. So basically, yes, anything I can eat with chopsticks, I will eat with chopsticks. If I can't, I'll use my spoon.

EL: Nice.

KK: We’re getting Thai takeout tonight. Now I'm really excited.

AC: I’m coming to your house.

KK: Sure, come on down. Although you know with all the COVID, I don't think Florida is really a place you want to be coming these days.

EL: So I guess this would be a good time to open the floor to questions. So Brian, I was thinking that I would be able to keep an eye on it, and I totally couldn't. So I'm glad that you were keeping an eye on it. So do you have any questions that our listeners would like to ask Annalisa?

Brian Katz: I’ve noticed three so far. One is from Joshua Holden, would Desargues’ theorem be useful for computer graphics?

AC: That’s a really good question. If I knew anything about computer graphics, I would be able to answer that better. I do know that my students who have gone on into computer engineering tell me that the course that I offered on projective geometry was one of their most useful courses, that this idea of ray tracing was was super, super helpful. So I don't know if Desargues’ theorem itself is specifically useful, but the idea of projective geometry is certainly how we understand the world through videos.

BK: We got a request from Doug Birbrower asking for you to hold up the line drawing while I asked the next one. I was wondering, so when we're talking about triangles, we have these vertices that are special points. How does this idea translate when you're talking about, say, shadows of more complicated objects that might be smooth? You talked a little about circles, but is there a special that happens when you generalize beyond polygons?

AC: One of the things that makes triangles really awesome is the same reason why triangular stools are so useful, is they're always stable, right? Whereas a four legged stool can wobble. If you try to draw the perspective image of an object With four points like a kite, it's really easy to make it be perspective from the sun without being perspective from a line. And if you do something like that, it'll look like maybe the kite is planar, but the shadow is curved, which might make sense on the ground. So in some ways, it's saying triangles really determine planes. Yeah, the question of drawing other curves is really interesting because of how you do or don't define curves in projective geometry. So one way you could think of a curve is a collection of points. You could also think of it as a collection of tangent lines. And so I think a way to generalize Desargues’ theorem to those would be to be talking about those collections of points and those collections of tangent lines.

BK: And then the third one that got some answers in in the chat was: I have a sense that, like, parallel things that when they're prospective from a point that means the point’s at infinity when we're talking about projective geometry. Is their geometric intuition about what it means for the line, perspective from a line, for that line to be infinity? And TJ suggested that it was that the objects are translations of each other.

AC: So if the line is it that that is at infinity, then either you could think of this as being translations, or you can think of it as being a dilation. And so it's a translation if both the axis where the two triangles meet is infinity and the center, that is what how you shine from one to another, is also off at infinity. And they’re are a dilation if the axis is off at infinity, but the center is what we call an ordinary point.

KK: This is new for us, having a Q and A. It's usually just the three of us, you know, me and Evelyn and whoever we're interviewing, but this is fun. I like this interaction.

EL: Yeah, I like that. And people have good questions. Yeah. Great. Thanks. Are there any more questions from the chat that we want to get to? Okay, looks like I'm seeing no. So I think this will sort of wrap up the…oh, Brian. Yeah.

BK: This one just appeared: Do cylindrical polar coordinates throw any light on this?

AC: Oh, so I was just about to say to everybody, “Thank you so much for asking me questions that I actually know the answers to!” And this one, I have no idea. I don't know. I don't know anything about cylindrical polar coordinates. Sorry. Now I'm going to write that one down and go check it out.

EL: But we can all appreciate the “throwing light” phrase of the question. That was very well done. Thank you.

KK: Clever.

EL: So, to wrap up the podcast portion of this, or the the episode with Annalisa portion of this, we will have show notes that are available. Our podcast listeners probably know where to find that at Kevin's website. And on that will include a link to your website, a link to the books that you have. Do you want to say the titles of the books that you've written that people might be interested in?

AC: So the first one, the one from 2011, is called Viewpoints with a subtitle “mathematical perspective, and fractal geometry in art,” and that's suitable for, like, a first-year seminar in math and art. So students don't need to really know anything at all about mathematics. And then the other one is called Perspective and Projective Geometry, and it came out in 2019.

EL: Yeah, so thank you for joining us, Annalisa. And for your doing it in this different fun format.

AC: I’m really flattered that you invited me to do this. Yeah, it's been so much fun trying to think about how to do this without drying gazillions of pictures. I appreciate that.

EL: Yeah.

KK: Thanks so much.

We were delighted to have a crossover event with Talk Math With Your Friends, an online math seminar that runs on Thursdays at 4 pm Eastern time. You can watch a video of this episode, which includes a collection of "flash favorite" theorems from the audience, here. Our guest for this episode was Annalisa Crannell from Franklin and Marshall College, who talked about Desargues' theorem. Below are some links you might find handy after listening to the episode.
Crannell's academic website
Her collaborator Fumiko Futamura's website 
Desargues' theorem on Wikipedia, which includes some helpful diagrams
The Image of a Square, a paper about the theorem that every quadrangle is a square if you look at it the right way. (Also available from Futamura's website.)
Viewpoints: Mathematical Perspective and Fractal Geometry in Art by Crannell and Mark Frantz
Perspective and Projective Geometry by Crannell, Frantz, and Futamura

During the episode, Crannell shared Bosse's original diagram for proving Desargues' theorem. It is here. Below is a version of the diagram colored in, making the triangles a little easier to see.

bosse-two-planes.jpg

Episode 56 - Belin Tsinnajinnie

Evelyn Lamb: Hello, My Favorite Theorem listeners. This is Evelyn. Before we get to the episode, I wanted to let you know about a very special live virtual My Favorite Theorem taping. If you are listening to this episode before July 16, 2020, you’re in luck because you can join us. We will be recording an episode of the podcast on July 16 at 4 pm Eastern time as part of the Talk Math With Your Friends virtual seminar. Join us and our guest Annalisa Crannell to gush over triangles and Desargues’s theorem. You can find information about how to join us on the My Favorite Theorem twitter timeline, on the show notes for this episode at kpknudson.com, or go straight to the source: sites.google.com/southalabama.edu/tmwyf. That is, of course, for “talk math with your friends.” We hope to see you there!

[intro music]

Hello and welcome to my favorite theorem, the podcasts that will not give you coronavirus…like every podcast because they are podcasts. Just don't listen to it within six feet of anybody, and you'll be safe. I'm one of your hosts, Evelyn Lamb. I'm a freelance math and science writer in Salt Lake City, Utah. And this is your other host.

Kevin Knudson: Hi. I’m Kevin Knudson, professor of mathematics at the University of Florida. So if our listeners haven't figured out by now, we are recording this during peak COVID-19…I don’t want to use hysteria, but concern.

EL: Yeah, well, we'll see if it’s peak concern or not. I feel like I could be more concerned.

KK: I’m not personally that concerned, but being chair of a large department where the provost has suddenly said, “Yeah, you should think about getting all of your courses online.” Like all 8000 students taking our courses could be online anytime now… It's been a busy day for me. So I'm happy to be able to talk math a little bit.

EL: Yeah, you know, normally my job where I work by myself in my basement all day would be perfect for this, but I do have some international travel plans. So we'll see what happens with that.

KK: Good luck.

EL: But luckily, it does not impact video conferencing.

KK: That’s right.

EL: So yeah, we are very happy today to be chatting with Belin Tsinnajinnie. Hi, will you introduce yourself?

Belin Tsinnajinnie: Yes, hi. Yá’át’ééh. Shí éí Belin Tsinnajinnie yinishyé. Filipino nishłį́. Táchii’nii báshishchíín. Filipino dashicheii. Tsi'naajínii dashinalí. Hi, everyone. Hi, Evelyn. Hi, Kevin. My name is Belin Tsinnajinnie. I'm a full time faculty professor of mathematics at Santa Fe Community College in Santa Fe, New Mexico. I’m really excited to join you for today's podcast.

EL: Yeah, I'm always excited to talk with someone else in the mountain time zone because it's like, one less time zone conversion I have to do. We're the smallest, I mean, I guess the least populated of the four major US time zones, and so it's a little rare.

BT: Rare for the best timezone.

EL: Yeah, most elevated timezone, probably. Yeah, Santa Fe is just beautiful. I'm sure it's wonderful this time of year. I've only been there in the fall.

BT: Yeah, we're transitioning from our cold weather to weather where we can start using our sweaters and shorts if we want to. We're very excited for the warmer weather we had. We're always monitoring the snowfall that we get, and we had an okay to decent snowfall, and it was cold enough that we're looking forward to warm months now.

EL: Yeah, Salt Lake is kind of the same. We had kind of a warm February, but we had a few big snow dumps earlier. So tell us a little bit about yourself. Like, where are you from? How did you get here?

BT: Yeah. I am Navajo and Filipino. I introduced myself with the traditional greeting. My mother is Filipino, my father is Navajo, and I grew up here in New Mexico, in Na’Neelzhiin, New Mexico, which is over the Jemez mountains here in Santa Fe. I went to high school, elementary school, college here in New Mexico. I went to high school here in Santa Fe. I got my undergraduate degree from the University of New Mexico, and I ventured all the way out over to the next state over, to University of Arizona, to get my graduate degree. While I was over there, I got married and started a family with my wife. We’re both from New Mexico, and one of our biggest goals and dreams was to come back to New Mexico and live here and raise our families where our families are from and where we're from. And when the opportunity presented itself to take a position at the Institute of American Indian Arts here in Santa Fe, it's a tribal college serving indigenous communities from all over the all over the nation and North America, I wanted to take that. I feel very blessed to have been able to work for eight years at a tribal college. And then an opportunity came to serve a broader Santa Fe, New Mexico community, where I also serve communities that are near and dear to my heart, where I've been here for over 30 years. And I'm really excited to have this opportunity to serve my community in a community college setting.

So, going into academia, and going into mathematics, it's not necessarily a typical track that a lot of people have opportunities to take on, but I feel very blessed to be doing math that I love serving communities that I love, and being able to raise my families around the communities that I love to. So I feel like you have a special kind of buy-in by engaging in a career that serves my communities and communities that are going to raise my families as well, too.

KK: That’s great.

EL: Nice. So I see over your shoulder a little bit of a Sierpinski triangle. Is that related to the kind of math you like to think about? Or is it just pretty?

BT: Yeah. One, it’s pretty. When I was at the Institute of American Indian arts, most of the students there, they're there for art. They come from Native communities, and they're not there to do mathematics, necessarily. So part of my excitement was to think about ways to broaden the ideas of mathematics and to build off of their creative strengths. And that piece is a piece that one of my students did. They did their own take on a Sierpinski triangle. I have a few of those items from my office where they integrated visual arts and integrated creative aspects of mathematics from cultural aspects as well, too.

KK: So I always think of Native American artists being kind of geometric in nature. It feels that way to me, I mean, at least the limited bit that I've seen. Is that sort of generally true?

BT: The thing about Native art is that Native cultures are diverse in and of themselves too. So there are over 500 federally-recognized tribes, and in Mexico are over 20 tribes alone, 20 nations alone, and each of them have their own notions of geometry and their own notions of their kinds of mathematics that they engage in with respect to the place that their cultures, their identities, and their languages are rooted in. So, yeah, a lot of it is visual, and geometric, because that's what we see. But there's also many I imagine that we don't see, that's embedded in the languages and the practices. Part of my curiosity is seeing how we can recognize what we do and what our traditions are, how we can recognize that as mathematical. And it might be mathematical in the sense that we, as professional mathematicians, might not be accustomed to seeing or experiencing. And, you know, I'm still trying to understand my own cultures, languages and traditions too. So I know mathematics more than a lot of how I experience my own culture. So on one hand, I'm seeing things from a traditional mathematician brought through academia, but I’m also trying to understand things through the lens of someone who's trying to better understand my cultures and histories.

EL: So what is your favorite theorem?

BT: The theorem I chose today was Arrow’s impossibility theorem.

KK: Nice.

EL: Great. And this will be a timely one, at least for the US, because it will be airing—I mean, I guess the past two years basically have been part of the 2020 presidential season—but really in the thick of it. So yeah, tell us a little bit about what this is.

BT: So I'll say more about why I'm kind of drawn to this theorem. So it's a theorem that basically says that there is no perfect ranked voting system, or no perfect way of choosing a winner and, by extension, for me, it kind of brings up conversations about how democracy itself isn’t perfect and that it's really hard to say that a democratic system can accurately represent the will of the people. And I was drawn to this theorem because as I started thinking about the cultural aspects of mathematics and mathematics education, I'm also interested in the power dynamics and the political dynamics and the sociopolitical aspects of mathematics and math education. And a lot of what's out there and written about math education talks about using quantitative reasoning and quantitative analysis and statistical analysis to really engage in critical dialogues and examining inequities and injustices in the world. And all of that is rich and engaging and needed and necessary ways that we can use mathematics to view the world. But the mathematician part of me still misses the definition-proof-lemma aspect of engaging in mathematics. So this theorem kind of represents a way of engaging in politics through some of the theorem-definition- lemma aspects of it. So the way that I understand Arrow’s theorem, and I mentioned this to you before, that I don't know the ins and outs of this theorem, I just really like the ramifications of it and the discussions that it generates. But it basically starts with the idea that we can describe functions where we're considering a way of choosing a winner of an election from a list of candidates. And we're taking each voter’s ranked preference of those candidates. So one thing that we're assuming is that each voter can rank a list of n candidates, A1 through An, and if everyone can rank their preferences, then a voting system would be a way to take all of those, those ranks, or those ballots, and choosing an overall ranking that is supposed to indicate an overall preference for the group of voters.

And what Arrow’s impossibility theorem talks about is that we want values, and want to describe good ways of what a good voting system is. So we want to describe list of criteria that shows that we have a good voting system. So the list of criteria that involves Arrow’s impossibility theorem talks about 1) and unrestricted domain; 2) social ordering; 3) weak Pareto or unanimity; 4) a non-dictatorship; and 5) independence of irrelevant alternatives. And I'll go through what each one means. So basically, an unrestricted domain means that we want a voting system or a way of choosing a winner to be able to take any set of ballots with any number of candidates and be able to give some overall ordering, that these functions are well-defined. So the unanimity condition talks about if everyone prefers one candidate over another, where every single voter has one candidate ranked over another candidate, then the overall function that turns the ballots into an overall social ordering should indicate that that candidate is preferred over the other candidate. And we also don't want a dictatorship, right? And the idea of that mathematically defined is that we don't want one voter deciding exclusively what the overall social ordering is of the candidates. And so we don't want a dictatorship. And we want an independence of irrelevant alternatives, and what that what a lot of people think about as an example of is a “spoiler” candidate or a third party candidate, where even if everyone prefers one candidate over another, that a change in order of a third or other candidate, without disrupting that other order, shouldn't change the overall outcome of an election. They relate that to how sometimes third party candidates can be a spoiler for an election even though overall, it looks like a plurality of voters might prefer one candidate over another. But certain voting systems can have that characteristic where third or other other set of candidates can disrupt the outcome of that election.

KK: I’ve never heard of that.

EL: Wouldn’t it be terrible if that ever happened? [Note: These statements were delivered somewhat sarcastically, presumably referring to the 2000 Presidential election in the US]

BT: Right, right, right. So what Arrow’s impossibility theorem says is that those all may be desired characteristics of a voting system or a social choice function, but that it's impossible to have all of those criteria in a voting system. So the general outline of the proof is that if we have a system that has the unanimity criterion, and an independence of irrelevant alternatives, that if we have those two criteria in a social choice function, then the voting system must be a dictatorship. So if we add those assumptions, then we can go through and show that there is a voter whose sole ordering determines the overall ordering of the voting group, of the voters.

KK: That’s how I always learned this theorem, is that you set down these minimal criteria, and the only thing that works as a dictatorship, right?

BT: Right.

KK: These criteria are completely reasonable, right?

EL: You can’t have it all.

BT: Right, right. They're not outlandish. They're what we might think of as things that we might value in a democracy. And, of course, these, these things don't perfectly replicate what's going on in the real world, but the outcome is still fascinating to me that mathematically, we can show that we can’t have all these sets of what we think are reasonable criteria in a voting system.

KK: Recently, maybe in the last two years, I’ve been getting interested in gerrymandering questions. And there's there's a similar sort of theorem that got proved in the last year or two, which essentially says that, you know, people don't like these sort of weird-shaped districts, they think that's bad somehow, because it's on unpleasing to the eye. But apparently — and there’s also this idea of the efficiency gap, where you sort of want to minimize wastage. So if you laid out some simple criteria, like you want compact districts, and you want to make the efficiency gap, minimized that, then the theorem is you have to have weird shape districts, right? So it’s sort of an impossibility theorem in that way too. So these these kinds of ideas propagate through all of these these kinds of systems,

EL: The real world is impossible.

BT: Right. And even by extension, you know, in many voting theory classes, there's a districting problem, which relates to a good metric for measuring compactness. But then the apportionment issue as well, that it's very hard, if not impossible, to find a fair way of apportioning a whole number of representatives that's proportionate to the state's population, relative to the overall population of the country.

KK: Yeah.

BT: And so yeah, this is one of my favorite theorems because it kind of opens the door to those conversations and gives me another way of thinking about when representatives, or people who talk about the outcomes of elections, say things like “the people have spoken,” “this is the will of the people,” “we have a mandate now,” that I think these outcomes really complicate those claims and should really give us a critical eye and a critical way of really discussing what the will of the people is, and how those discourses really perpetuate the idea that voting, and voting alone, can accurately indicate the will of the people and that that's to be accepted, and that we move forward with them.

EL: Yeah. So have you gotten to use these Arrow’s paradox or any of these other things in classes?

BT: When I was at the Institute of American Indian Arts, I tried to develop a voting theory class. And we got into that and talked about that. And it interested me too because the voting system on the Navajo Nation, we vote for our own council and our own presidents too, and I use this as a way to think about how we have a certain candidate in Navajo Nation who's always running and is seemingly unpopular. And the voting system for president in Navajo Nation is that we have that two-party runoff system where we vote for our top choices and that the top two vote getters participate in a general runoff election. And for a few consecutive elections, this one candidate that is seemingly unpopular just gets enough votes to get into the top two for the runoff election and then gets overwhelmingly outvoted in the general election. So I think for me it was a fascinating way to engage in these kind of mathematical ideas, or mathematical discourses, while talking about some of the real outcomes that are going on in our nations, in our communities, in our efforts towards our self-determination and sovereignty. So I wanted to tie in something that's mathematical, where we can talk about mathematical discussions, with issues that are contemporary and real to our, our peoples.

EL: It’s something I always wonder about is, you know, we've got a theorem that says voting is impossible — or it says that, you know, it's impossible to actually say, like, this is the will of the people. But do you know if much research has been done about, like, real sets of choices that people have and what voting systems might be — do they really experience this paradox, or in the real world, do they have these strange orders of preferences that that confound ranked choice voting rarely?

BT: I imagine that there is research out there and there are people who have engaged in it much more than I have. But something that makes me curious are some of the underlying assumptions that go into Arrow’s theorem and what has been mathematized as necessary criteria, and the values that those might be representative of for certain groups of people. For example, I guess you could call it an axiom of many these voting theory theorems in mathematics is that one voter is one vote, and you know, there are systems where that might not be true. But one of your criteria is one person, one vote. And that one person votes for their own interests and their own interest only, and there are extensions of these criteria where if we have other non-ranked voting systems, then it can help.

But let me backtrack: one of the outcomes of Arrow’s theorem is that when people know that it's impossible for the outcome to really represent the will of the people, then it could result in people voting for candidates other than their first option because they know that voting for someone other than their true option because we election in favor of something that's not of their desire. So we have people voting against their own actual first choices. And that happens with ranked-choice voting, and some of the extensions of these conversations have been about voting systems that don't require ranked choice. So perhaps giving each candidate a rating, and it helps alleviate some of those issues with ranked-choice voting, and it helps alleviate those issues of third-party candidates, where you can still give your candidate five stars out of five, like an Amazon review, but still really give perhaps a better indication of your true view of the candidates, rather than a linear ranking. So it kind of reveals that there are some issues with just linear ranking of candidates, when the way that we think about in value and understand our preference of candidates might be much more complex than a simple 1 through n ranking. But kind of going back to what I think this could mean for communities and other societal perspectives, is in many democracies, that one vote-one choice is kind of an assumption that that's what we want. But for many communities, perhaps we want to vote for something that does benefit an overall view of the people. What would that look like as a criteria if we allowed for something like that? What would we do if we allow criteria, or embedded in our definitions, some way of evaluating how if when we register a vote, that we're all not only taking into account our own individual interests, but the interests of our land, of our communities, of our nations. So those are cultural values that are not assumed in the current conversations, but for many communities in many Indigenous nations, those are some things that are real and necessary to think about. What would that look like if we expand those and then be critical of those assumptions that are underlying these current conversations on voting theory in mathematics.

EL: So one of the other things we do on this podcast is We ask our guests to pair their theorem with something. What have you chosen to pair with this theorem?

BT: I have a ranking of three pairings.

EL: Great. I’m so glad! Excellent.

BT: So I have 1-2-3. So I'll give my third choice first. The third out of three pairings: green chili cheeseburgers.

EL: Okay.

BT: And in New Mexico, everyone has their favorite place to get a green chili cheeseburger, and we take pride in our green chili, and every year any contest about the green chili cheeseburger and who has the best green chili cheeseburger causes some conversation, and it causes some controversy and rich discussions over who has the best green chili cheeseburger. So, I think about that as a food that has a lot of controversy as to who has the best green chili cheeseburgers in New Mexico. The second pairing is another food item, the Navajo taco.

EL: Oh yeah. Those are good.

KK: What’s in those?

BT: So, well, what we call a Navajo taco is a piece of frybread with toppings often involving meat and cheese, with lettuce and tomato and maybe some chili. And this is another controversial discussion in Native communities because we call it a Navajo taco, but it's not just Navajos who make this kind of dish, because many communities make their own versions of frybread. And so some places call it Indian tacos, and there's a lot of controversy over which community first introduced the Navajo taco and why some people call it the Navajo taco and others call it Indian tacos. And so in Native communities, there's a lot of controversy over what constitutes the best version of this dish. And the other reason I'm pairing that is the frybread itself comes from a time where it was created out of necessity for survival, where the flour that had been rationed out to our communities was rancid, and in order to actually make it edible, it was deep fried. And so on one hand, it represents a point in time where our communities were just fighting for survival, and it also represents their ingenuity, and became a part of our everyday practice. But at the same time, it's a reminder that that was something that was imposed on our communities, much like voting systems nowadays. It's an act of our survival and our sovereignty, the voting systems that we have in place. But I think there's also need to come back and have other conversations about what's good for our communities.

And the first-ranked pairing is mathematics itself with Arrow’s theorem. So we have a lot of conversations about how mathematics is universal, mathematics is for everyone, that everyone can do mathematics, and that everyone can participate in mathematics. But for many people from from equity, justice and diversity perspectives, we want to be critical about who has access to mathematics, whose ideas of mathematics are represented in our mainstream ways of thinking about mathematics. Just like we think about democracy as being the will of the people and being a representation of all the people, that Arrow’s is kind of a critique of that notion of democracy. And I think mathematics, we can take a lesson from this theorem and think about what we mean when we say mathematics is universal or mathematics is for everyone or mathematics is for all, when this term itself is kind of a democratic take on mathematics, that everyone can do mathematics, and everyone can be an equal participant in mathematics. But, you know, we think the same thing about democracy, and this theorem says that there are some issues with that. So I'm interested in seeing how we can take this lesson and how we can think about how we can be more critical about the ways we think about mathematics itself.

EL: Yeah, well, you know, Arrow’s paradox is not about this, but we have issues with people who can't vote for various reasons and should be able to vote, or places that shut down polling places in certain communities to make it so people have to stand in line for six hours. Which is, you know, not easy to do if you've got a job that you need to get to. So yeah, there's so much richness. I love that you paired a ranking of three things with this. And now I feel like we should also vote on these, but I just don't think it's fair for one of them to be math. I mean, you’ve got two mathematicians here, three mathematicians here in total. I think it's going to be a blowout.

KK: No, tacos win every time, don’t they?

EL: I should have known.

KK: This is a really good pairing. I like this a lot.

EL: Yeah.

KK: We also like to give our guests a chance if they want to plug anything. Where can we find you online for example, or can we?

BT: Probably the best way to find me is on Twitter. My Twitter handle is @lobowithacause.

EL: Yeah. You'll see him popping up everywhere. Is that the mascot for the University of New Mexico?

KK: It is, the lobos.

EL: And I believe a talk that you gave at the Joint Math Meetings, is there video of that available somewhere?

BT: I was told that there would be video. I haven't found it yet. There was a video recorded. And I'll follow up with that and see that it gets out. I'll make an announcement on Twitter.

KK: I’ve noticed those have been trickling out kind of slowly. It'll show up, I think.

EL: Yeah, we'll try to dig it up by the time we put the show notes together so people can watch that. Unfortunately, I was still making my way to Denver when that happened, so I didn't get to see it. So selfishly I very much want to see it. I heard really good things about it. So thank you so much for coming on here and giving us a lot to think about.

BT: Oh, it was an honor. And you know, I love your podcasts.

KK: Thanks so much.

BT: I love what you’re doing. I had fun in listening to your other podcasts in preparation for this and loved hearing Henry Fowler and shout out to Moon Duchin too. I heard that you, Kevin, went to that gerrymandering work in Boston a few years ago. I was there too. And I had a great week there.

EL: Oh, nice.

KK: That was a big workshop. There was no way to meet everybody. Yeah,

EL: Thanks for joining us, and have a good rest of your day.

BT: Thank you. Thank you. You too.

In this episode of the podcast, we were happy to talk with Belin Tsinnajinnie, a professor at Santa Fe Community College, about Arrow's impossibility theorem, which basically says that a perfect voting system is impossible. Below are some links you might enjoy as you listen to the episode.
Arrow's impossibility theorem
Cardinal voting, an alternative to voting systems that are based on ranking the options
Our episode with Henry Fowler, who was at the time on the faculty of Diné College and is now at Navajo Technical University
Our episode with Moon Duchin, who studies gerrymandering, among other things
Belin Tsinnajinnie on Twitter

Episode 55 - Rebecca Garcia

Evelyn Lamb: Hello and welcome to my favorite theorem. Math podcast. I'm one of your hosts Evelyn Lamb. I'm a freelance math and science writer in Salt Lake City, Utah. And this is your other host.

Kevin Knudson: Hi. I’m Kevin Knudson, professor of mathematics at the University of Florida. How's it going?

EL: All right, it is a bright sunny winter day today, so I really like—I mean, I'm from Texas originally, so I'm not big on winter in general, but if winter has to exist, sunny winter is better than cloudy winter.

KK: Sure, sunny winter is great. I mean, it's a sunny winter day in Florida, too, which today means it is currently, according to my watch, 81 degrees.

EL: Oh, great. Yeah.

KK: Sorry to rub it in.

EL: Fantastic. It is a bit cooler than that here.

KK: I’d imagine so.

EL: So yeah. Anything new with you?

KK: No, no. Well, actually so so my I might be going to visit my son in a couple of weeks because he's studying music composition, right? And the the orchestra at his at his university is going to play one of his pieces, and so kind of excited about that.

EL: Very exciting! Yeah, that's awesome.

KK: Yeah, but that's about it. Otherwise, you know, just dealing with downed to trees in the neighborhood. Not in our yard, luckily, but yeah, stuff like that. That's it.

EL: Yeah. Well, we are very happy today to have Rebecca Garcia as a guest. Hi, Rebecca. How are you?

Rebecca Garcia: Hi, Evelyn. Håfa ådai, I should say, håfa ådai, Evelyn, and håfa ådai, Kevin. Thanks for having me on the program.

EL: Okay, and what—håfa ådai, did you say?

RG: Yeah, that's right. That's how we, that's our greeting in Chamorro.

EL: Okay, so you are originally from Guam, and is Chamorro the name of a language or the name of a group of people, or I guess, both?

RG: It’s both actually. Yes. That's right. And so Chamorro is the native language in the island. But people there speak English mostly, and as far as I'm able to tell I think I'm the first Chamorro PhD in pure mathematics.

EL: Well, you’re definitely the first Chamorro guest on our show. I think the first Pacific Island guest also.

KK: I think that's correct. Yeah.

EL: So yeah, how did you—so you currently are not in Guam. You actually live in Texas, right?

RG: I do. I'm a professor at Sam Houston State University, which is in Huntsville, Texas, north of Houston. And I'm also one of five co-directors of the MSRI undergraduate program.

EL: Oh, nice. That seems like it is a great program. So how did you how how did you get from Guam to Huntsville?

RG: Oh my goodness. Wow. That is a that is a long, long journey.

KK: Literally.

RG: I started out as a as a undergraduate at Loyola Marymount University, and I had the thought of becoming a medical doctor. And so I thought we were supposed to do some, you know, life science or you know, chemistry or biology or something along those lines. And so I started out as one of those majors and had to take calculus and fell in love with calculus and the professors in the math department. And I was drawn to mathematics. And that's how I ended up on the mathematics side. And one of the things that I learned in my undergraduate career was these really crazy math facts about the rational numbers. And so that's one of the things that interested me in mathematics, was just the different types of infinities the concept of countable, uncountable, those sorts of things.

EL: Yeah, those those seem to be the kinds of facts that draw a lot of people into this rich world of creativity and math that you might not initially think of as related to math when you're going through school. So I think this brings us to your favorite theorem, or at least the favorite theorem you want to talk about today.

KK: Sounds like it.

EL: Yeah, so what’s that?

RG: Yeah. So it’s more, I would say, more of a fun fact of mathematics that the rationals first of all are countable, meaning they are in one-to-one correspondence with the natural numbers. And so you can kind of, you know, label them, there's a first one and a second one in some way, not necessarily in the obvious way. But then, at the same time, they are dense in the real numbers. So that to me, just blows my mind, that between any two real numbers, there's a rational number.

EL: And yeah, so you can't like take a little chunk of the real line and miss all the rational numbers.

RG: That’s right.

KK: Right.

RG: That to me just blows my mind. Because—and then you just sort of start, you know, your brain just starts messing with you, you know, between zero and one there are infinitely many rational numbers and yet they're still countable. And it just, it just starts to mess with your mind a little bit. Right?

EL: Yeah. Well, and we were we were talking about this a little bit before and it's this weird thing. Like, yeah, there's, like a countable is like a smallness thing. And yet dense is like, they're, you know, they fill up the whole interval this way. I mean, it is really weird. So where did you first encounter this?

RG: This was in a class in real analysis. And, yeah, so that's where I started to…I thought I was going to be a functional analyst. I thought I was that's what I wanted to do this. I love real analysis. That didn't happen either. But it was in that class where we were talking about just these strange facts, like the Cantor set: that set is a subset of the reals that is uncountable and yet it’s sparse.

KK: Totally disconnected, as the topologists say.

RG: Totally disconnected. There you go. Yeah. Right. And so then all these weird things are happening. And you're just in this world where you thought you understood the real line, and then they throw these things at you like, the reals are dense. I mean, the rationals are dense in the reals, you have these weird uncountable sets that are totally disconnected. What's going on? Yeah, so that's where I started to hear about all these weird things happening.

KK: Right. So one of two things happens when people learn these things, right? It either blows their minds so much they can't keep going. Or it intrigues them so much that you want to learn more. But not be an analyst. Right?

RG: [laughing] That’s right. At some point I fell in love with computational algebraic geometry and these Gröbner bases, and how you can really get your hands on some of these things and their applications to combinatorics. So I ended up, I had an algebraist’s heart, but I was exposed to some really good analysts early in my career. And so I was very confused. But I've always, I stay true to my algebraic heart and follow that mostly.

EL: And so is this a fact that you get to teach to your students now ever?

RG: So no, this is not, but I do like to talk about the the different infinities and things along those lines. And I like to, before class I come in early, and I'll have a little chat with them about just the fact that—you know, they they don't understand that math is not “done.” So, there's still so much to do. And they have no idea that, you know, there's what, what is research like? What does that mean? And so I talk about open questions. And I bring some of that in the beginning of class. And these concepts that had also drawn me in, about the different kinds of infinities and these weird concepts about the rationals being dense and, you know, just things like that. I do get to talk about it, but it's not in a class that I would teach the material on.

EL: Yeah, just going back to this idea that you've got the rationals that are dense, so it's this, like, measure zero small set, but it's like everywhere. And then you've got the Cantor set, which is uncountable and sparse. It's like, we've got these various ways of measuring these sets. And you think that they line up in some natural way. And yet they don't. It's just like, you know, the density is measuring a different type of property of the numbers than the measure is.

RG: That’s exactly.

EL: And actually, I guess countability is a different thing. Also, I mean, it's, yeah, it's so weird. And it's hard to keep all these things straight. My husband does a lot of analysis and like has, yeah, all of these, like, what kinds of sets are what.

RG: And what properties they have. And yeah, I don’t have that completely straight.

KK: This is why I’m a topologist.

EL: But I mean, topology is like,

KK: Oh, it's weird too.

EL: It’s secretly analysis.

KK: Well…

EL: Analysis wishes it was topology, maybe.

KK: So my old undergraduate advisor—who passed away last summer, and I was really sad about that—but he always he always referred to topology as analysis done right.

EL: Shots fired.

KK: Which is cheap, of course, right? Because you prove all this stuff in topology Oh, the image of a connected set is connected. Yeah, that's easy now go off to the real line and prove that the connected sets are the intervals. That's the hard part. Right? So yeah, he's being disingenuous, but it was. It's a good line. Right.

RG: Right.

EL: So you said that you ran into this, was this an undergraduate class where you first saw these notions of countability and everything?

RG: Right, it was an undergraduate class where I ran into those notions and I was a junior, well, I guess it was in my second semester as a junior, where we were talking about these strange sets. And that's when I had also thought about going on to graduate school and wanting to do mathematics for the rest of my life. I mean, I was a major by then, of course, but I just didn't know what I was going to do. But it wasn't until then, when I learned about, well, this is this could be a career for you. This may be something you like to do. And of course, this was many, many years ago. And nowadays, you can do so much more with mathematics, obviously. I mean, we know that we can do so much more, I should say. We've always been able to do so much more. We just haven't been able to share that with our students so much. We never really spent the time to let them know there's so many careers and mathematics that one can do. But anyway, at that, at that time I was I was drawn into really thinking about becoming a mathematician, and that was one of the experiences that that made me think that there's so much more to this than than I originally thought.

EL: Yeah, well, I talk to a lot of people, you know, in my job writing and doing podcasts and stuff about math, and there's so many people who don't realize that, like, math research is a career you can do.

RG: Right.

EL: And the more we can share these kinds of “aha” moments and insights, the better and, you know, just show like, well, you can use, you know, kind of the logic and the rules of the game to like, find out these really surprising aspects of numbers.

RG: Right. And I think also, one of the experiences that I've had as an undergrad that really just sort of sealed the deal—I’m going to go into mathematics—was doing an undergraduate research program as a student. Well wasn't really at the time an undergraduate research program, it was just another summer program. This is many years ago, almost before all of that. And I had the chance to spend a summer just thinking about mathematics at a higher level with a cohort of other students who were like-minded as well, you know. And it was really—it was it was like, “Oh, I can do this for the rest of my life? Like how amazing is that?” And so, I was part of a summer program as an undergrad. And then when I was a graduate student, my lifelong mentor, Herbert Medina, was running a program in Puerto Rico and asked me to be a TA while I was a grad student. And so these were some of the things that led me to do what I do now, working with undergraduates, doing research and mathematics.

EL: And so that ties in to the MSRI program that you are part of, right?

RG: Right.

EL: I guess it I've seen it written like MSRI-UP. So I guess that's undergraduate program?

RG: Yes. Undergraduate Program. That's right. Yeah. Well, that that's sort of like, a different stage that I'm at now. But yeah, before that, I started my own undergraduate research program together with colleagues in Hawaii, at the University of Hawaii at Hilo. And we ran an undergraduate research program called PURE Math, and that was Pacific Undergraduate Research Experience in Mathematics. And we ran that for five years. And then, and then I ended up moving into the co-director role at MSRI-UP.

EL: Nice.

KK: That’s a great program.

EL: Yeah. So the other thing we like to ask our guests to do, is to pair their theorem with something. You know, just like the right wine can enhance that meal, you know, what would you recommend enjoying the density of the rationals with?

RG: Well, I did think about this a bit. And one of the things that I think, you know, you think the rationals are dense but they really shouldn't be? So, I think of foods that are dense, but they really shouldn't be, and one of those foods that comes to mind, especially being here in Texas, but also being married to a mathematician who is from Mexico, is tamales. So tamales really should not be dense. They should be fluffy and sumptuous, but here in Texas, you find really dense the most, unfortunately. But it It was strange to also discover that growing up in Guam, we also have our own version of tamales, and a lot of the foods are related in some way to foods from Mexico. So I feel like there's this huge rich connection between myself being from Guam, my husband being Mexican and there's just this strange richness that we share this culture, that I don't know, it just blows my mind too. So the same way that the rational is being dense in the reals blows my mind.

EL: All right, well, I have to ask more about this tamale like creation from in traditional Guam cuisine. What, is that wrapped in, like, banana leaves or something like that?

RG: It ought to be, and maybe traditionally it was. I think that nowadays it's not that way. They usually serve it in aluminum foil, and it's made—it's a mixture like tamales. So tamales in Mexico are made with corn, right?

KK: I was about to ask this. What are they made of in Guam?

RG: Yeah, yeah. And so in Guam we actually use, like, a rice product.

EL: Okay.

RG: It's ground up just like corn. And so instead of corn, we're using rice, and it's flavored in different ways.

KK: Interesting.

EL: All right. I have kind of in my mind because I'm more familiar with this like almost, is it kind of like a mochi texture? Because, I mean, that's a rice product, but maybe it's not maybe that's like more gelatinous than this would be.

RG: Yeah, I guess mochi is really pounded and yeah, so yeah, that's more chewy. I think that the tamal, well, you wouldn't say it like that, but the tamales in Guam are very soft and, gosh, I don't know how to describe it. But it's a very soft textured food.

KK: I would imagine the rice could be softer, and I mean, corn can get very dense, especially when you start to put lard in it and things like that.

RG: Yes.

KK: I mean, it’s delicious.

RG: It is delicious. And oh my, I can’t get enough tamales. Oh, well.

KK: Yeah, maybe you can.

RG: Yeah, I should learn.

EL: Yeah, well, nice. I unfortunately, we do have a couple restaurants in Salt Lake that are Pacific Island restaurants, but we have more people from Samoa and Tonga here. I don't know if we have a lot of people from Guam here. Yeah, there's actually like a surprising number of like, Samoans who live in Salt Lake. Who knew?

RG: Right.

EL: But yeah, it's it's because of like the history of Mormon missionaries.

KK: That’s what I was gonna say.

EL: Yeah, the world is very interesting, but yeah I don't know if I've seen this kind of food there. I will just have to, you know, if I'm ever in Huntsville I’ve got to get you to make me some of this. I’m just inviting myself over for dinner now. Hope you don't mind.

RG: That would be great. It would be wonderful to have you here.

EL: Is there anything else you'd like to share? We'd like to give our guests a chance to like, share, you know if they've got a website or blog or book or anything, but also if you want to share information about MSRI-UP, application information, anything like that for students? Anything you'd like to share?

RG: Oh, wow. That's a lot of stuff.

EL: Yeah, I know. I just rattled off a ton of things.

RG: Well, yes, I do have, I guess I would like to say for the undergraduate listeners in the audience, please consider applying to our MSRI-UP program, and just in general apply to a research program in the summer. These are paid opportunities for you to expand your mind and do some mathematics in a great environment, and so I highly recommend considering applying for that. And so this is the time right now of course by the time the listeners hear this, I’m sure it will be over, but consider doing some undergraduate research or using your summer wisely.

KK: I parked cars in the summer in college. I did.

EL: Well, you never know the connections that might happen though because I was talking to someone one time who basically his big break to get to go to grad school came because, like, somehow he was involved in like parking enforcement somewhere, and some math professor called in to complain about, like, getting a ticket, and one thing led to another and then he ended up in grad school. So really, you never know. Maybe that's not the ideal route to take. There are more direct routes, but yeah, there are many paths.

RG: Yes, there are. And there's also another, I guess another thing to flag would be, well, contributed to a book that Dr. Pamela Harris and others have put together on undergraduate research. So that just I guess that was just released. I'm not entirely sure now. I think it was accepted, and I don't know if if one is able to purchase it, but if you if you consider working with your students on undergraduate research, this is a great resource to use to get you going, I guess.

KK: Great.

EL: Oh, awesome. So this is like a resource for like faculty who want to work with undergraduates? Oh, that's great.

RG: Yes.

EL: We will find a link to that and put that in the show notes for people.

RG: That sounds good.

EL: Okay, great. Thanks so much for joining us.

KK: It’s been great.

RG: Thank you so much.

On this episode of My Favorite Theorem, we were happy to talk with Rebecca Garcia, a mathematician at Sam Houston State University, about the density of the rational numbers in the reals. Here are some links you might find helpful.

Her website
A biography of Garcia for SACNAS
MSRI-UP 
A Project-Based Guide to Undergraduate Research in Mathematics, the book she mentioned contributing to

Episode 54 - Steve Strogatz

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast and so much more. I'm Kevin Knudson, professor of mathematics at the University of Florida, and here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a freelance math and science writer based in Salt Lake City, where it is snowy, but I understand not as snowy as it is for our guest.

KK: I know, and we've been trying to make this one happen for a long time. So I'm super excited that this is finally going to happen. So today we are pleased to welcome Professor Steve Strogatz. Steve, why don't you introduce yourself?

Steve Strogatz: Well, wow, thank you. Hi, Kevin. Hey, Evelyn. Thanks for having me on. Yeah, I've wanted to be on the show for a very long time. And I think it's true what Evelyn just said, we have a very big snowstorm here today in not-so-sunny Ithaca, New York, upstate. I just took my dog out for a walk, and the snow was over my boots and going into them and making my feet wet.

KK: See, I have a Florida dog. She wouldn't know what to do. Actually, we were in North Carolina a few years ago at Christmas, and it snowed, and she was just alarmed. She had no idea what to do. And she's small, too, she just couldn't take it.

SS: Yeah, well, it would be more like tunneling than running.

KK: Right.

EL: Yeah. So we actually met quite a few years ago at this point — actually, I know the exact date because it was, like, two days before my brother's wedding the first time we met because you were on the thesis committee for my sister in law, who is a physicist, many years ago, and so we have this weird, it was when I had just moved to New York to work at Scientific American for the first time. So it was at the very beginning of my life as a math writer. And I remember just being floored by how generous you were with being willing to meet with a nobody like me.

SS: Well that’s nice.

EL: At this time when I was first starting.

SS: But actually, I had a crystal ball, and I knew you were going to become the voice of mathematics for the country, practically. I mean, so I let me brag on Evelyn’s behalf a little bit. If you go on Twitter, you—I wonder if you know this, Kevin, do you know this little factoid I'm going to unreel?

KK: I bet I do.

SS: You know where I'm going. On Twitter, if you ask “What mathematician do other mathematicians follow?” I think Evelyn is the number one person the last time I checked.

KK: She is indeed number one. That's right.

SS: Yeah.

EL: I like to say I'm the queen of math, Twitter, although I don't actually like to say this because it feels really weird.

SS: Well that’s okay. You didn't say it. But yeah, I do remember our meeting that day in my office. And right, it was on this happy occasion of a family, of a wedding. Okay, sorry, I interrupted you, Kevin.

KK: Oh, I don't know. I was going to say with the Twitter thing. I think you're not far behind, right? Like, aren't you number two, probably?

SS: I think the last time I looked I was number two.

KK: Yeah.

SS: So look at that. Okay, so look at that, the two tweet monsters here.

KK: And now the funny thing is I'm not even on that list. So here we go.

SS: Okay. Yeah, well you could catch up. I'm sure you'll be coming right on our heels.

KK: Maybe. I have over 1000 followers now, but apparently not that many mathematicians. So this is how this goes. Anyway, what weird times we live in, right?

SS: It's very weird. I mean, I don't know what this can get us, a cup of coffee or what.

KK: Maybe, maybe. Okay. Let's talk theorems. So Steve, you must have a favorite theorem. What is it?

SS: Yeah, I have a very sentimental attachment to a theorem and complex analysis called Cauchy’s theorem, or sometimes called Cauchy’s integral theorem.

KK: Oh, I love that theorem.

SS: It’s a fantastic theorem. And so I don't know. I mean, I feel like I want to say what I like about it mathematically and what I like about it personally. Does that work?

EL: Yeah, that’s exactly what we want.

SS: Well, okay. So then, the scene is, it's my sophomore year of college. Maybe I'll start with the emotional.

KK: Okay.

SS: It’s my sophomore year of college. I've just gotten very demoralized in my freshman year, taking the the honors linear algebra course that a lot of universities offer as a kind of first introduction to what college math is really going to be like. You know, a lot of kids in high school have done perfectly well in their precalculus and calculus courses, and then they get to college and suddenly it's all about proofs and abstraction. And it can be—I mean, we sometimes call it a transition course, right? It's a transition into the rigorous world of pure math. And so it was a shock for me. I had a lot of trouble with that course. I couldn't read the book very well, it didn't have pictures. And I'm kind of visual. And so I was always at a loss to figure out what was going on. And being a freshman I didn't have any sense about, why don't I look at a different book, you know, or maybe, maybe I should switch sections. Or I could ask my teaching assistant, or I could go to office hours. I didn't know to do any of that stuff.

So anyway, this is not my favorite theorem. I was very demoralized after this experience in linear algebra. And then when I took a second semester, also an honors course, that was a rigorous calculus course with the Heine-Borel theorem, and, you know, like, all kinds of—again, no formulas, it was all about, I remember hearing this stuff about “every open cover has a finite subcover,” and I thought, “I want to take a derivative! I can't do anything here. I don't know what to do!” So anyway, after that first year, I thought, “I don't have the right stuff to be a mathematician. And so maybe I'll try physics,” which I also always loved. I say all that as preamble to this complex analysis course that I was taking in sophomore year, which, you know, I still wanted to take math, I heard complex variables might be useful for physics, I thought it would be an interesting course. I don't know. Turned out it was a really great course for me because it really looked a lot like calculus, except it was f(z) instead of f(x).

KK: Right.

SS: You know, but everything else was kind of what I wanted. And so I was really happy. I had a great teacher, a famous person actually named Elias Stein.

KK: Oh.

SS: So Stein is a well-known mathematician, but I didn't know that. To me, he was a guy who wore Hush Puppies and, you know, had always kind of a rumpled appearance, came in with his notes. And he seemed nice, and I really liked his lectures. But so one day, he starts proving this thing, Cauchy’s theorem, and he draws a big triangle on the board. And he's going to prove that the integral of an analytic function f around this triangle is zero no matter what f is. All he needs is that it's analytic, meaning that it has a derivative in the sense of a function of a complex variable. It's a little more stringent condition—actually a lot more stringent than to say a function of a real variable is differentiable, but I didn't appreciate that at the time. I mean, that's sort of the big reveal of the whole subject.

KK: Right.

SS: That this is an unbelievably stringent condition. You can’t imagine how much stuff follows from this innocuous-looking assumption that you could take a derivative, but okay, so I'm kind of naive. Anyway, he says he's going to prove this thing, only assuming that f is analytic on this triangle and inside it. And that's enough. And then, you know, I feel like you don't have enough information, there's nothing to do! So then he starts drawing a little triangle inside the big triangle, and then little triangles inside the little triangle. And it starts making a pattern that today I would call a fractal, though I didn't know it at the time, and he didn't say the word fractal. And actually, nobody ever says that when they're doing this proof. But it’s—right, they don’t—but it's triangles inside of triangles in a self-similar way that doesn't actually play any particular role in the proof, other than it's just this bizarre move, like, What is going on? Why is he drawing these triangles inside of triangles? And by the end, I mean, I won't go into the details of the proof, but he got the whole thing to work out, and it was so magnificent that I started clapping.

And at that point, every kid in the room whipped their head around to look at me, and the professor looked at me, like what is wrong with you? You know, and yet, I thought, “Wow, why are you guys looking at me?” This was the most amazing theorem and the most amazing proof.” You know, so anyway, to me, it was a very significant moment emotionally because it made me feel that math was, first of all, something I could do again, something I could appreciate and love, after having really been turned off for a year and having a kind of crisis of confidence. But also, you know, aside from any of that, it's just, I think people who know would regard this proof —this is actually by a mathematician named Goursat, a French mathematician who improved on Cauchy’s original proof. Goursat’s proof of Cauchy’s theorem is just one of the great— you know, it's from “The Book” in the words of Paul Erdős, right? If God had a proof of this theorem, it would be this proof. Do you guys have any thoughts about that? I mean, I'm assuming you know what I'm talking about with this theorem and this proof.

KK: Well, this is one of my favorite classes to teach because everything works out so well. Right? Every answer is zero because of Cauchy’s theorem, or it's 2πi because you have a pole in the middle, right?

SS: Yeah.

KK: And so I sort of joke with my students that this is true. But then the things you can do with this one theorem, which does—you’re right, it's very innocuous-looking, you know, you integrate an analytic function on a closed curve, and you get zero. And then you can do all these wonderful calculations and these contour integrals and, like, the real indefinite integrals and all this stuff. I just love blowing students’ minds with that, and just how clean everything is.

EL: Yeah, I kind of—I feel like I go back and forth a little bit. I mean, like, in my Twitter bio, it does have “complex analysis fangirl.” And I think that's accurate. But sometimes, like you said, it's so many of these, you know, you're you're like teaching it or reading it and you're like, “Oh, this is complex analysis is so powerful,” but in another way, it's like our definition of derivative in the complex plane is so restrictive that like, we're just plucking the very nicest, most well-behaved things to look at and then saying, “Oh, look what we can do when we only look at the very most well-behaved things!” So yeah, I kind of go back and forth, like is it really powerful or are we just, like, limiting ourselves so much in what we think about?

KK: And I guess the real dirty secret is that when you try to go to two complex variables, all hell breaks loose.

SS: Ah, see, I've never done that subject, so I don't appreciate that. Is that right?

KK: I don't, either. Yeah. But I mean, apparently, once you get into two variables, like none of this works.

SS: Ohhh. But that's a very interesting comment you make there, Evelyn, that—you know, in retrospect, it's true. We've assumed, when we make this assumption that a function is analytic, that we are living in the best of all possible worlds, we just didn't realize we were assuming that. It seems like we're not assuming much. And yet, it turns out, it's enormously restrictive, as you say. And so then it's a question of taste in math. Do you like your math really surprising and really beautiful and everything works out the way it should? Or do you like it thorny and full of rich counterexamples and struggles and paradoxes? And I feel like that's sort of the essential difference between real analysis and complex analysis.

EL: Yeah.

SS: In complex analysis, everything you had dreamed to be true is true, and the proofs are relatively easy. Whereas in real analysis, sort of the opposite. Everything you thought was true is actually false. There are some nasty counterexamples, and the proofs of the theorems are really hard.

EL: Yeah, you kind of have to MacGyver things together. “Yeah, I got this terrible epsilon and like, you know, it's got coefficients and exponents and stuff, but okay, here you go. I stuck it together.

KK: But but that's interesting, Steve, that this is your favorite theorem because, you know, you're very famous for studying kind of difficult, thorny mathematics, right? I mean, dynamics is not easy.

SS: Huh, I wouldn't have thought that, that's interesting that you think that. I don't think of myself as doing anything thorny.

KK: Okay.

SS: So that's interesting. I mean, yes, dynamical systems in the hands of some practitioners can be very subtle. I mean, those are people who have a taste for those those kinds of issues. I've never been very sophisticated and haven't really understood a lot of the subtleties. So I like my math very intuitive. I’m on the very applied end of the applied-pure spectrum, so that sometimes people will think I'm not really a mathematician at all. I look more like a physicist to them, or maybe even, God forbid, a biologist or something. So yeah, I don't really have much taste for the difficult and the subtle. I like my math very cooperative and surprising. I like—well, not surprising for mathematical reasons, but more surprising for its power to mirror things in the real world. I like math that is somehow tapping into the order in the world around us.

EL: Yeah, so this it's interesting to me, also that you picked this because, yeah, as you say, you are a very applied mathematician. And I think of complex analysis as a very pure—I actually, I'm trying to not say “pure” math, because I think it's this weird, like, purity test or something. But you know, that like a very theoretical thing. So does it play into your field of research at all?

SS: Well, uh, not particularly. Yeah. So that's a good question. I mean, I have to say I was a little intimidated by the title of the podcast. If you ask me what's my favorite theorem, the truth is for me, theorems are not my favorite things.

KK: Okay.

SS: My favorite things are examples or mathematical models. Like there’s a model in my field called the Kuramoto model after a Japanese physicist Yoshiki Kuramoto. And if you asked me what's my favorite mathematical object, I would say the Kuramoto model, which is a set of differential equations that mirrors how fireflies can get their flashes in sync, or how crickets can chirp in sync, or how other things in nature can self-organize into cooperative, collective oscillation. So that's my favorite object. I've been studying that thing for 30 years. And I suppose there are theorems attached to it, but it's the set of equations themselves and what they do that is my favorite of all. So I don't know, maybe that's my real answer.

KK: Well, that’s fine. So yeah, it's true. We've had people who've done that in the past, they didn't have a favorite theorem, but they had a favorite thing.

SS: But still, I mean, I am still a mathematician, part of me is, and I do have theorems that I love, and one of the things I love about Cauchy’s theorem is that in the proof, with this drawing of all the nested triangles inside the big triangle, you end up using a kind of internal cancellation. The triangles touch other triangles except on their common edge, sometimes you're going one way, and sometimes you're going in the opposite direction on that same edge. And so those contributions end up cancelling. And you end up, the only thing that doesn't cancel is what's going on around the boundary. And then that can be sort of pulled all the way into a tiny triangle in the interior, which is where you end up using the local property that is the derivative condition to get everything that you need to prove the result about the big triangle on the outside.

But the reason I'm going into all that is that this is a principle, this internal cancellation, that is at the heart of another theorem that's been featured on your show, the fundamental theorem of calculus, which uses a telescoping sum to convert what's happening on the boundary to what's happening when you integrate over the interior. This idea of telescoping I think, is really deep. I mean, it's what we use to prove Stokes’ theorem. It's what we would use to prove all the theorems about line integrals. It comes up in topology when you're doing chains and cochains. So this is a principle that goes beyond any one part of math, this idea of telescoping. And I've been thinking I want to write an article, someday (I haven't written it yet) called “Calculus Through the Telescope” or “A Telescopic View of Calculus” or something like that, that brings out this one principle and shows its ramifications for many parts of math and analysis and topology. I think some people get it, people who really understand differential forms and topology know what I'm talking about. But no one ever really told me this, and I feel like maybe it should be mentioned, even though it is well-known to the people who know it.

KK: Right, it's the air we breathe, right? So we don't we don't think about it.

SS: I guess, but like, I think there are probably high school teachers, or others who are teaching calculus—like for instance, when I learned about telescoping series in my first calculus course, that's just seems like a trick to find an exact sum of a certain infinite series of numbers. You know, they show you, “Okay, you could do this one because it's a telescoping series.” And it seems like it's an isolated trick, but it's not isolated. This one idea—you can see the two- dimensional version of it in Cauchy’s theorem, and you can see the three-dimensional version of it in the divergence theorem, and so on. Anyway, so I like that. I feel like this idea has tentacles spreading in all directions.

EL: Yeah. Well, this makes me want to go back and think about that idea more because, yeah, I wouldn't say that I would necessarily have thought to connect it to this many other things. I mean, you did preface your statement with “those who really understand differential forms,” and my dark secret is that the word “form” really scares me. It's a tough one. It's somehow, that was one of those really hard things, when I started doing more, like, hard real analysis. It's like, I feel like I always had to just kind of hold on to it and pray. And you get to the end of it. You're like, “Well, I guess I did it.” But I feel like I never really got that full deep understanding of forms.

SS: Huh. I don't I don't claim that I have either. I'm reminded of a time I was a teaching assistant for a freshman course for the the whiz kids that—you know, every university has this where you throw outrageous stuff at these freshmen, and then they rise to the occasion because they don't know what you're asking them to do is impossible. But so I remember being in a course, like I say, as a teaching assistant, where it was called A Course in Mathematics for Students of Physics, based on a book by Shlomo Sternberg, at Harvard, and Paul Bamberg, who's a physicist there too, and a very good teacher. And that book tried to teach Maxwell's equations and other parts of physics with the machinery of differential forms and homology and cohomology theory to freshmen. But what was amazing is it sort of worked, and the students could do it. And in the course of teaching it, I came to this appreciation of integrating forms, and how it really does amount to this telescoping sum trick. And, anyway, yeah, it's true, that maybe it's not super widely appreciated. I don't know. I don't know if it is, I don't want to insult people who already know what I'm talking about. But I I do feel like there's a story to tell here.

KK: Okay. Well, we'll be looking for that.

EL: Yeah.

SS: Someday.

KK: In the New York Times, right?

SS: Well.

KK: So another thing we do on this podcast is we ask our guests to pair their theorem with something. And we might have sprung this on you, but you seem to have thought of a solution here. So what have you chosen to paired with Cauchy’s theorem?

SS: Cubist painting.

KK: Oh, excellent. Okay. Explain.

EL: Yeah, tell us why.

SS: Well, I'm thinking of Cubism. I don’t—look, I don't know much about art. So it might be a dumb pairing. But what I'm thinking is there's a there's a painting. I think it's by Georges Braque of a guy, or maybe it's Picasso. Someone walking down stairs. And maybe it's called a Nude Descending a Staircase, or something like that. You're nodding, do you know what I mean?

EL: I'm a little nervous about saying, I think it is Picasso, but I'm looking it up on my phone surreptitiously.

SS: I could try too. For some reason, I'm thinking it's George Braque, but that may be wrong. But so I'll describe the painting I have in my head and it may be totally not—

EL: No, it’s Marcel Duchamp!

SS: Oh, it's Marcel Duchamp?

EL: Yeah.

SS: And what's the name of it?

EL: Nude descending a staircase, number two. I think.

SS: Yeah, that's the one. Would that be considered Cubism?

EL: Yeah.

SS: It says according to Wikipedia, it’s widely considered a modernist classic. Okay, I don't know if it's the best example of what I'm thinking. But it's, let me just blow it up and look at it here. So, what hits me about it is it's a lot of straight lines. It's very rectilinear. And you don't see anything that really looks curved like a human form. You know, people are made of curved surfaces, our faces, our cheeks are, you know. What I like is this idea that you can build up curved objects out of lots of things made of straight lines. You know what you can do? mesh refinement on it. For instance, there's an old proof of the area of a circle where you chop it up into lots of pizza-shaped slices, right, and then you add up the areas of all those. And they can be approximated by triangles, and if you make the triangles thin enough, then those slivers can fill out more and more of the area, the method of exhaustion proof for the area of a circle. So this idea that you can approximate curved things with triangles, reminds me of this idea in Cauchy’s theorem that you first you prove it for the triangle, and then later Professor Stein proved the result for any smooth curve by approximating it with triangles, you know, a polygonal approximation to the curve, and then he could chop up the interior into lots of triangles. So I sort of think it pairs with this vision of the human form and it's sinuous descent down. You know, this person is smooth and yet they're being built out of these strange Cubist facets, or other shapes. I mean, think of other Cubist paintings you you represent smooth things with gem-like faceted structures, it sort of reminds me of Cauchy’s theorem.

KK: Okay, good pairing. Yup.

EL: Yeah, glad we got to the bottom of that before we made false statements about art on this math podcast.

SS: Yeah, it may not be the best Cubist example. But what are you gonna do? You invited a mathematician.

KK: So we also like to let our guests make pitches for things that they're doing. So you have a lot going on. You have a new podcast.

EL: Yeah, tell us about it.

SS: Okay. Yeah, thank you for mentioning it. I have a podcast with the confusing name Joy of X. Confusing because I also wrote a book by that name. And before that I had written an article by that name.

KK: Yes.

SS: So I did not choose that name for the podcast. But my producer felt like it sort of works for this podcast because it's a show where I interview scientists and mathematicians—in spirit, very similar to what we're doing here. And I talk to them about their lives and their work. And it's sort of the inner life of a scientist, but it could be a neuroscientist, it could be a person who studies astrophysics, or a mathematician. It's anything that is covered by Quanta Magazine. So Quanta Magazine, some of your listeners will know, is an online magazine that covers fundamental parts of math and science and computer science. Really, it's quite terrific. If people haven't read it, they might want to look at it online. It's free. And anyway, so Quanta wanted to start a podcast. And they asked me to host it, which was really fun because I get to explore all these parts of science. I've always liked all of the different parts of science, as well as math. And so yeah, that's the show. It's called the Joy of X where here, X takes on this generalized meaning of the unknown, not just the unknown in algebra, but anything that's unknown, and the joy of doing science and the scientific question. We'll be sure to link to that.

EL: Yeah.

KK: Also, I think Infinite Powers came out last year, right? 2019?

SS: That’s true. Yes, I had a book, Infinite Powers, about calculus. And that was an attempt to try to explain to the general public what's so special about calculus, why is it such a famous part of math. I try to make the case that it really did change the world and that it underpins a lot of modern science and technology as well as being a gateway to modern math. I really do think of it as one of the greatest ideas that human beings have ever come up with. Of course, that raises the question, did we discover it or invent it? But that’s a good one.

EL: Put that on a philosophy podcast somewhere. We don’t need that on this math podcast.

SS: Yeah, I don't really know what to say about that. That's a good timeless question. But anyway, yes, Infinite Powers was a real challenge to write because I'm trying to tell some of the history, but I'm not a historian of math. I wanted to really teach some of the big ideas for people who either have math phobia or who took calculus but didn't see the point of it, or just thought it was a lot of, you know, doing one integral after another without really understanding why they're doing it. So it's my love song to calculus. It really is one of my favorite parts of math, and I wanted other people to see what's so lovable and important about it.

KK: Yeah.

SS: The book, as I say, was hard because I tried to combine history and applications and big ideas without really showing the math.

KK: Yeah, that's hard.

SS: And make it fun to read.

KK: Right. It is. It's a very good book, though. I did read it.

SS: Oh, thanks.

KK: And I enjoyed it quite a bit.

EL: Well, it is on my table here under a giant pile of books to read, because people need to just stop publishing.

SS: That’s right.

EL: There’s too much. We just need to have a year to catch up, and then we could start going again but what's what's

KK: What’s that Japanese word, sort of the joy of having unread books? [Editor’s note: Perhaps tsundoku, “aquiring reading materials but letting them pile up in one’s home without reading them.”] There's a Japanese concept of like these books that you’ll, well, maybe even never read. But that you should have stacks and stacks of books. Because, you know, maybe you'll read them. Maybe you won't. But the potential is there.

SS: Nice.

KK: So I have a nightstand, on the shelf of my nightstand there's probably 20 books there right now, and I haven't read them all. I've read half of them, maybe, but I'm going to read them. Maybe.

SS: Yeah, yeah.

KK: Actually, you know, when you were talking about your sort of emotional feelings about Cauchy’s theorem, it reminded me of your—I don't know if it was your first book, but The Calculus of Friendship, about your relationship with your high school teacher.

SS: Well, how nice of you to mention it.

KK: Yeah. That was interesting to it, because it reminded me a lot of me, in the sense of, I thought I knew everything too when I was 18. Like, I thought, “Calculus is easy.” And then I get to university and math wasn't necessarily so easy. You know. And so these same sort of challenges, you know?

SS: Well, I appreciate that, especially because that book is pretty obscure. As far as I know, not many people read it. And it's very meaningful to me because I love my old teacher, Mr. Joffrey, who is now, let’s see, he's 90 years old. And I stayed in touch with him for about 35 years after college, and we wrote math problems to each other, and solutions. And it was really a friendship based on calculus. But over the course of those 35 years, a lot happened to both of us in our lives. And yet, we didn't tend to talk about that. It was like math was a sanctuary for us, a refuge to get away from some of the ups and downs of real life. But of course, real life has a way of making itself, you know, insinuating itself whether you like it or not. And so it's it's that story. The subtitle of the book is “what a teacher and a student learned about life while corresponding about math.” And I sometimes think of it as, like, there's a Venn diagram where there's one circle is people who want to read math books with all the formulas, because I include all the formulas from our letters.

KK: Yeah.

SS: And then there's people who want to read books about emotional friendships between men. And if you intersect those two circles, there's a tiny sliver that apparently you're one of the people in it.

KK: And your book might be the unique book in that in that Venn diagram too.

SS: Maybe. I don't know. But yeah, so it was it was clear it would not be a big hit in any way. But I felt like I couldn't do any other work until I wrote that book. I really wanted to write it. It was the easiest book to write. It poured out of me, and I would sometimes cry while I was writing it. It was almost like a kind of psychoanalysis for myself, I think, because I did have a lot of guilty feelings about that relationship, which, you know, if you do read the book, anyone listening, you'll see what I felt guilty about, and I deserved to feel guilty. I needed to grow up, and you see some of that evolution in the course of the book.

KK: Yeah. All right. Anything else you want to pitch? I mean?

SS: Well, how about I pitch this show? I mean, I'm very delighted to be on here. Really, I think you guys are doing a great thing helping to get the word out about math, our wonderful subject. And so God bless you for doing that.

KK: Well, this has been a lot of fun, Steve, we really appreciate you taking time out of your snow day. And so now do you have to shovel your driveway?

SS: Oh, yeah, that may be the last act I ever commit.

KK: Don’t you still have a teenager at home? Isn't that what they're for?

SS: My kids, I do have—you know what, that's a good point. I have one daughter who is still in high school and has not left for college yet, so maybe I could deploy her. She's currently making oatmeal cookies with one of her friends.

KK: Well, that's a useful, I mean that that's helping out the family too, right? I mean,

SS: They’re both able bodied, strong young women. So I should get them out there and with me, and we could all shovel ourself out. Yeah.

KK: Good luck with that. Thank you. Thanks for joining us.

SS: My pleasure. Thanks for having me.

On this episode of My Favorite Theorem, we were happy to talk with Steve Strogatz, an applied mathematician at Cornell University, about the Cauchy integral theorem. Here are some links you might find helpful.

Strogatz’s website, which includes links to information about his books and article
The Joy of X, the podcast he hosts for Quanta Magazine
The Cauchy integral theorem on Wikipedia
The Kuramoto model
Nude Descending a Staircase no. 2 by Marcel Duchamp

Episode 53 - Ruthi Hortsch

Evelyn Lamb: Hello and welcome to My Favorite Theorem, the podcast that was already quarantined. I’m one of your hosts, Evelyn Lamb. I am holed up in my house in Salt Lake City, Utah, where I'm a freelance writer. So, honestly, I have worked in my basement, you know, every day for the past five years, and that hasn't changed. This is your other host.

Kevin Knudson: Hi, I’m Kevin Knudson, professor of mathematics at the University of Florida, which is open for business…But you can't go to campus.

EL: Okay.

KK: Yeah, we moved all of our classes online two weeks ago, I'm just teaching a graduate course this term, so that's sort of easier for me. I feel bad for the people who have to actually lecture and figure out how to do this all at once. My faculty have actually been great. They really stepped up. And, remarkably, I've had very few complaints from students, and I'm the chai,r so you know, they would come to me. And it's just really not—I mean, everybody has really taken the whole thing in stride. A lot of anxiety out there, though, among our students. Really, this is a really challenging time for everybody. And I just encourage my faculty to, you know, be kind to their students and to themselves. So let’s shelter in place and get through this thing, right?

EL: Yup. Yeah, we had an earthquake a week and a half ago to just, like, shake things up, literally. So it's just like, oh, as if I pandemic sweeping through town was not enough. We'll just literally shake your house for a while.

KK: Yeah, well, you know, we can go outside. We have a Shelter in Place Order, but it's been 90 degrees every day for the last week. And so you know, I like to go bird watching, but my favorite bird watching spot is a city park, and it's closed. So I have to just kind of sit on my back porch and see what's up. Yeah. Oh, well,

EL: Well, yes, we're making it through it. And I hope—I mean by the time this is—we have a bit of a backlog in our past episodes, and so who even knows what's going to be happening when this is airing. [Editor’s note: We decided to publish this one out of order, so we actually recorded it pretty recently.] But whatever is happening, I know our guests will be very thrilled to be listening to Ruthi Hortsch! Hi, Ruthi. How are you today?

Ruthi Hortsch: Hey, I'm managing.

EL: Yeah.

RH: It’s a weird time.

EL: Definitely. So what do you do, and where are you?

RH: Yeah, so I'm in New York City right now, which is kind of right now the hotbed of lots of new infections. But I've been in my apartment for the last two and a half weeks and haven't really directly been experiencing that.

I work for an organization called Bridge to Enter Advanced Mathematics. So we're a education nonprofit. We work with low-income and historically marginalized youth. And we're trying to create a realistic pathway for them to become mathematicians, scientists, engineers, programmers.

We start working with students when they're in middle school and we try to figure out, like, what are the things you need to get you to a place where you'll have a successful STEM career? And so we do a lot of different things, but they all are to that purpose.

EL: Yeah, and I'm so glad that we have you on the show to talk about this. Because, yeah, I've been thinking like, we really need to get someone from BEAM on here because I think BEAM is just such a great program. My spouse, and I donate to it every year. I mean, obviously not every year, I don't even know how old it is. But you know, we've made that part of our yearly giving, and yeah, I just think it does great work. So, does that have programs in both New York and LA now?

RH: Yes. So we started in New York City in 2011. And a few years ago, we expanded to LA. So the LA programs are still pretty new. They're building up, kind of starting with students in the first year of contact, and then adding in programming for the older students as that first class gets older. So they now have eighth graders, and that's their oldest class, and they'll continue to add in the ninth grade and the 10th grade program, et cetera, as it goes on. The other kind of exciting thing is, last year, we got a grant from the Gates Foundation. And that grant was to partner with other local programs and other cities to help them build up programs that could do some of the same things we do. So it's not the same comprehensive, really intensive support that we give our students in New York City and LA. But assuming summer camps don't get canceled this summer because of corona, there are going to be day camps in Albuquerque and Memphis that are advised by us.

EL: Oh, that's so great. Yeah, because that's the one thing about it is that it is so localized and, of course, important places for it to be localized. But, you know, the more the, the wider, the better. So that's awesome. And what's your role there? What do you do?

RH: Yeah, I have a hard time answering this question. So I work in programs, which is like, I work on things that are directly affecting students. I run one of our summer camps in the summer. So I run a sleepaway camp at Union College, in which students learn proof-based mathematics for the first time. The students at the sleepaway camp are all rising eighth graders, and so they get to learn number theory and combinatorics and group theory. They also do some modeling and programming and stuff.

During the year I do some managing our other programs team, so supporting other staff. I also do all of our faculty hiring. So certainly we hire a lot of people just for the summer, and most of them are—so we hire college, university students, we hire grad students, we hire professors in various different roles. And I handle all of the, like, hiring people to teach math courses.

EL: Wow.

KK: That’s a lot. Are your programs sort of face to face, or are they online? Is it sort of a combination of stuff?

RH: Yeah, so our summer we run six in-person summer camps each summer. So there's two in upstate New York that are sleepaway, one in Southern California that's sleepaway, and then one day camp in LA and two day camps in New York City. And those are all in-person, face to face. And then during the school year, we also have Saturday classes, which is a mix of life skills and enrichment. And we also do in-person advising. So we have office hours where students can come ask us anything, and then also kind of more intensive. Like, how do you apply to college? How do you get into other summer programs or other STEM opportunities? So most of our programs are face to face. Right now, we've had to cancel a bunch of our year-round stuff. So we don't have Saturday classes right now. We are doing one class for the eighth graders virtually, because we really thought it was critical. And at the moment, we're hoping the summer programs will still run, but it's really hard to say what's going to be going on in two weeks.

KK: Yeah, well, fingers crossed.

EL: But as wonderful as it is to talk about BEAM, what we're dying to know is what is your favorite theorem?

RH: Yeah, so this was actually really fast for me to think of. My favorite theorem is Falting’s theorem. So Falting’s theorem is also actually known as the Mordell conjecture, because Mordell originally conjectured it in the same paper in which he proved Mordell’s theorem, I believe, or at least during the same process of research for him.

EL: Yeah, and so for longtime listeners, was it Mathilde Lalín who, that was her favorite theorem?

RH: Mm-hmm.

EL: Okay, that's right. So we're kind of dovetailing right in.

RH: Yeah. So Mordell’s theorem is about—so when you look at elliptic curves, they have a finitely-generated abelian group. And Mordell’s theorem is the theorem that proves that it actually is finitely-generated.

KK: Right.

RH: So when I say the finitely-generated part, it's actually only looking at the rational points on the curve. So we care about algebraic curves, kind of in general. And then we want to think about, like, how do different algebraic curves behave differently? And because I'm trained as a number theorist, I also specifically care about how many rational points are on that curve and how they behave. So this intersects also with algebraic geometry. And in some sense, this is a statement about how the arithmetic part of the curves—the rational points—interacts with the geometry of it.

So one thing that people care about a lot in geometry is the notion of a genus. This is one of the ways to classify things. And of course, when you're looking at visual shapes, one way of thinking about the genus is how many holes does it have? So if you're just looking at a shape that’s, like, a big sphere, there's no way of poking a hole through it without actually breaking it apart. And so that has genus zero because there are zero holes. But if you're looking at a doughnut, a torus, that has one hole because there's like one place where you can poke something through. And then you can generalize from there that having more holes is higher genus. And so that's kind of a wishy-washy way of looking at things, and a very visual way. There are ways to define that formally in the algebraic sense, but in the places where both definitions make sense, the definition is the same.

And so when you look at algebraic curves, we can ask ourselves, how do genus zero curves act differently than genus one curves, act differently than genus two curves, and does that tell us anything about the number of rational points? And so it turns out that with genus zero curves, genus zero curves are actually really just conic sections. So basically the nice lines that you study in like algebra in high school. And those have infinitely many rational points, right? So when I say rational point, you can kind of think of it as being like the points where the components have rational values.

And genus one curves are actually exactly elliptic curves. So in that case, that's when Mordell’s theorem kicks in and the rational points are this finally generated abelian group. And sometimes they have infinitely many rational points, and sometimes they don't, and it kind of depends on what this algebraic structure, this algebraic group structure, looks like. So that's the most complicated weird point. And for genus two or higher curves, it turns out to be true that there are only finitely many rational points on a genus two or higher curve. And that's the statement of Falting’s theorem.

EL: Okay, and so I, there's something that I, you know, you hear like genus two or higher. And I always wonder, is there a limit to how high the genus can be of these curves? Or, like, is there a maximum complexity that these curves can have?

RH: So no. And actually, there's a statement in algebraic geometry that makes it really easy-ish— you know, “ish”— to calculate the genus, which is called Riemann-Roch. And it gives you a relationship between the degree of the equation defining it and the genus. And essentially, the genus grows quadratically with the degree. There's an asterisk on everything I'm saying. It’s mostly true.

KK: It’s mostly true.

EL: So if I'm remembering correctly, Mordell’s—let’s see, Mordell’s conjecture, Falting’s theorem—was really important for proving Fermat’s last theorem. Is that correct?

RH: I don't think so, no. But all of these things are related to each other.

EL: Okay.

RH: A lot of the common definitions and theorems that play into all these things, they share a lot, but it's not directly, like, one thing implied the other.

EL: Okay, yeah.

RH: In particular, Fermat’s Last Theorem was reduced to a statement about elliptic curves, which is about genus one curves, while Falting’s theorem is really a statement about genus two or higher curves.

EL: Okay.

KK: So was this a love at first sight kind of theorem?

RH: I think no. I think part of the reason that I really started appreciating it was because I had a mentor in undergrad who was really excited about it. And I didn't really understand the full implications and the context, but I was like, “Okay, this mentor I have is really about it, so I'm going to be really about it.”

And we actually used Falting’s theorem as a black box for the REU project I was working on. So we assumed it was true and then used that to show other things. And then later on in grad school, I had a number of things that I was really interested in that Falting’s theorem was related to. One of the things that I think is really cool that's being researched right now is there’s a bunch of like, tropical geometry that is being studied. And this is, like, relating algebraic verbs to kind of more combinatorial objects. So you can actually translate these lcurves that have a more—I don't want to say analytic, but a smooth structure, and then turning them into a question about, like, counting more straight-edged structures instead.

One of the things about Falting’s proof of Falting’s theorem is that it's not, it doesn't actually give you a bound. So it tells you that there are only finitely many points, but it doesn't give you a constructive way of saying, like, what does it actually bounded by, the number of finite points? And using tropical geometry, people have been able to make statements about bounds in certain situations, which is really cool.

KK: Okay, I always like these tropical pictures, you know, because suddenly everything just looks almost like Voronoi diagrams in the plane, these piecewise linear things. So I guess the idea of genus probably still makes sense there in some way, once you define it properly. Right?

RH: Yeah. And there's a correspondence between, there’s a notion of a tropical curve, which still looks like one of those Voronoi diagrams. There’s an actual correspondence, this curve in classical algebraic geometry gives you this particular diagram.

EL: Nice. And so you say it was very easy to choose this theorem. So what's your, like, elevator sales pitch for this theorem? Keeping in mind that no one is going to be in an elevator with anyone else anytime soon. We're staying far apart, but you know.

RH: Yeah. So, I think it’s kind of amazing that geometry can tell you something about the arithmetic of a curve. I think this is what drew me to arithmetic algebraic geometry, that there is this kind of relationship. When you think, okay, arithmetic, geometry, those are totally different fields, people study them in totally different ways, but in fact, it turns out that the geometry of a curve can tell you information about the arithmetic. And that's just bizarre, and also very powerful in that you can make a statement about how many rational solutions there are to an equation using correspondence in geometry.

The REU project that I worked on actually is a statement that I think is really easy to understand. If you have a rational polynomial, that gives you a function from the rationals to the rationals, right?

And so you can ask yourself: how many-to-one is that function? How many points gets sent to the same point? And if you look at only rational points, our REU project showed that it can't be more than four-to-one off a finite number points.

So if you are willing to ignore some finite number of points, then no rational polynomial is ever more than four-to-one.

KK: Interesting.

RH: And that feels like a very powerful statement. And it's because we had this hammer of Falting’s theorem to just smash it in the middle.

KK: That’s really fascinating. So no matter how high the degree it's no more than four-to-one? I wouldn’t have guessed that.

RH: Off a finite number of points.

KK: Yeah, sure. Generically. Yeah. Right. Interesting.

RH: I think the real powerful thing there is that Falting’s theorem comes in.

KK: Yes.

RH: Oh, actually, higher degree means high complexity means high genus.

KK: Okay, cool. So another thing we like to do is ask our guests to pair their theorem with something. So what pairs well with Falting’s theorem?

RH: Yeah, so this is a maybe a little bit of a stretch, but I've been living in New York City for four years, and I love bagels. They’re definitely one of the best parts of living in New York City. I'm always two blocks away from a really good bagel. Traditionally, bagels are genus one, so it's actually not quite appropriate. You have to, I don't know, do the fancy cut to increase the genus—there’s a way to cut a bagel to get higher genus. But I still think since we're thinking about genuses, we're thinking about complexity of things.

EL: Yeah. Well, like, you cut the bagel in in half, you know, to get like the cream cheese surface, and then just stick them together and you've got a genus two. Put a little cream cheese on the side. You know?

RH: Yeah. I mean, if we're cutting holes we can cut as we want.

EL: That’s true. So, are you more—what do you put on the bagel? What kind of bagel, also, do you prefer?

RH: Ao I mostly like everything bagels.

EL: Of course. Yeah. Great bagel.

RH: There is a weird thing that goes on where some bagel shops put salt on their everything bagel and some don't. And I feel like the salt is important.

KK: Yeah. Agree.

EL: As long as it's not too much. Like just the right amount of salt is—

RH: Yeah. It’s definitely important.

KK: Well a salt bagel is a pretzel.

EL: Yes.

RH: And I don't actually eat cream cheese. So I do eat fish sometimes, but I generally don't eat dairy. And I so I usually get, like, tofu scallion spread. And the tofu spread that gets sold in the bagel shops here is actually really good.

KK: Well yeah, I'm not surprised. I can't get a decent bagel in Gainesville. I mean, there's a couple of bagel shops, but they're no good.

RH: Yeah. This is what you get for leaving New York City.

KK: Right, right.

EL: Yeah, it's funny, actually one of our quarantine projects we're thinking about is making bagels. I've made bagels one other time. But, yeah.

KK: It's kind of a nuisance. You know that. That boiling step is really—I mean, it's crucial, but it just takes so much time and space.

EL: Yeah, I mean, they were not nearly as good as a real bagel shop bagel, but fun to play with.

KK: Yeah. So what's everyone doing to keep themselves occupied? So far I've got a batch of sauerkraut fermenting. I just started a batch of limoncello that'll be ready in a month. I made scones. Maybe that’s it. Yeah. How about you guys?

RH: Well, I'm still trying to work 40 hours a week.

KK: Yeah, I'm doing that too.

RH: We're still trying to help our students respond to the crisis and helping support them both academically, but holistically also.

KK: Yeah, it's very stressful.

RH: And at the moment, we're still doing all of our prep work for the summer, which is a huge undertaking? But when I have free time, I've been cooking more. And I'm actually also working on writing a puzzle hunt.

EL Ooh, cool. Well if that happens, we'll include a link to that in the show notes—if it's the kind of thing that you can do out of a particular geographical place.

RH: Yeah, so the puzzle hunt I'm helping write is actually for Math Camp.

EL: Okay.

RH: So before I worked for BEAM I worked for Canada-USA Math Camp, and in theory, they're running a camp this summer, and one of the traditional events there is [the puzzle hunt]. I think the puzzle hunt often gets put up after the summer, but I’m not sure.

EL: Oh, cool. The last thing that I, or library book that I got out from the library—it was actually supposed to be due, like, the day after the library shut down here—was 660 Curries, which is an Indian cookbook that—we don’t really cook meat at home, but it's got, I don't know, maybe a hundred-page section of legume curries and a bunch of vegetable curries, so we've been kind of working through that. We made one last night that was great. It was a mixture of moong dal and masoor dal. Yeah, we’ve been eating a lot of curry, and it just makes my early-this-year plan of, like, “Oh, I want to make more dal, so I've got to go stock up on lentils and rice,” brilliant plan, really has made it a lot easier. So yeah.

RH: I love dal, and I don't feel like anybody around me ever likes dal as much as I do.

KK: This is a dal-lover convention right here. It's one of my favorite things to eat. Yeah.

EL: Oh, yeah. Well, I can recommend, if you get a chance to get 660 Curries, I don't remember if it's called mixed red and lentil dal with garlic and curry leaves, or something like that.

KK: Yeah, I'm actually making curry tonight, but chicken curry so we'll we'll see.

EL: Yeah, so other than that, just panicking most of the time. It’s been a big pastime for me.

RH: I’ve had to, like, ban myself from reading the news in the evening.

KK: Good call.

EL: That is very smart.

RH: I haven’t done a good job keeping to it.

EL: Yeah, I have not done a good job with my self-control with that. So, I’m really trying to do that. I'm hoping to do some sewing projects too, maybe making some masks that I can leave out for people in the neighborhood to take. Obviously not medical grade, but maybe make people feel a little better.

KK: So yeah, Ellen, my wife, started doing that yesterday. She made, you know, probably 15 of them yesterday real quick.

EL: Nice.

KK: I went to the store yesterday and you know—

EL: Hopefully it gives people a little peace of mind and maybe decreases droplet transmission.

KK: Let’s hope.

EL: I’ve refrained from armchair epidemiology, which I encourage everyone to do. So yeah, I hope everyone stays safe and tries to keep keep a good spirit and help the people in your lives. I hope our listeners can do that too. And I hope they find some enjoyment in thinking about math for a little while with us.

KK: So yeah, thanks for joining us, Ruthi. We really appreciate it.

EL: Yeah, everyone go find BEAM online if you want to learn more about that.

RH: Yeah. Follow us on social media.

EL: Yeah. So what are the handles for that?

RH: Yeah, I should have this memorized. You can find it on our website. They're all linked to on our website, beammath.org. If you're in New York or LA, we have trivia night, which is a puzzle-y, mathy trivia, usually in the fall, that you can buy tickets to. So I definitely recommend that. And otherwise, sign up for our newsletter, which you can also do on our website.

EL: And you're on Twitter also, right?

RH: Yes, I am. You do have to know how to spell my last name, though.

EL: Okay.

RH: Yeah, I'm @ruthihortsch.

EL: All right. And that's H-O-R-T-S-C-H?

RH: Good job!

EL: Yeah, it’s funny, I was actually in a Zoom spelling bee last night. So yeah, I got second place.

KK: Good for you.

EL: Got knocked out on diaphoresis.

KK: Diaphoresis. Wow. Yeah, that's pretty—okay, anyway. All right. Well, thanks for joining us and take care everyone.

RH: Right. Yeah, it was nice to meet you.

EL: Bye.

[outro]

On today's episode of My Favorite Theorem, we had the privilege to talk with Ruthi Hortsch, a program coordinator at Bridge to Enter Advanced Mathematics (BEAM), a math program for low-income and historically marginalized middle- and high-school students. Dr. Hortsch lives in New York City, which is currently being hit hard by covid-19. We love all our listeners and guests, and right now we are especially thinking about those in New York and other virus hot spots. You may be sick, you may be worried about loved ones, you may be suddenly parenting or caregiving in ways you hadn't expected. We wish you the best, and we hope you enjoy thinking about math for a little bit instead of the news cycle. Stay strong and healthy, friends!

As you listen to this episode, you may find these links helpful.
The Bridge to Enter Advanced Mathematics websiteTwitterFacebook, and Instagram pages.
Ruthi Hortsch on Twitter
Faltings’s theorem, Dr. Hortsch's favorite theorem
Our episode with Matilde Lalín, whose favorite theorem was the closely-related Mordell's theorem.
660 Curries

Canada/USA Mathcamp

Tropical Geometry wikipedia page

Episode 52 - Ben Orlin

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast. I'm Kevin Knudson, professor of mathematics at the University of Florida. And here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a freelance math and science writer, usually based in Salt Lake City, but currently still in Providence. I'll be leaving from this semester at ICERM in about a week. So trying to eat the last oysters that remain in the state before I leave and then head back.

KK: Okay, so you actually like oysters.

EL: Oh, I love them. Yeah, they're fantastic.

KK: That is one of those, it’s a very binary food, right? You either love them—and I do not like them at all.

EL: Oh, I get that, I totally get it.

KK: Sure.

EL: They’re like, in some sense objectively gross, but I actually love them.

KK: Well, I'm glad you've gotten your fill in. Probably—I imagine they're a little more difficult to get in Salt Lake City.

EL: Yeah, you can but it’s not like you can get over here.

KK: Might be slightly iffy. You don't know how long they've been out of the water, right?

EL: Yeah. So there's one place that we eat oysters sometimes there, yeah, that's the only place.

KK: Yeah, right. Okay. Well, today we are pleased to welcome Ben Orlin. Ben, why don't you introduce yourself?

Ben Orlin: Yeah, well, thanks so much for having me, Kevin and Evelyn. Yes, I'm Ben Orlin. I’m a math teacher, and I write books about math. So my first book was called Math with Bad Drawings, and my second one is called Change Is the Only Constant.

EL: Yeah, and you have a great blog of the same name as your first book, Math with Bad Drawings.

BO: Yeah, thank you. And I think our blogs are, I think almost birthday, not exactly but we started them within months of each other, right? Roots of Unity and Math with Bad Drawings.

EL: Oh, yeah.

BO: Began in, like, spring of 2013 which was a fertile time for blogs to begin.

EL: Yeah. Well, in a few years ago, you had some poll of readers of like, what other things they read and, and stuff and my blog was like, considered the most similar to yours, by some metric.

BO: Yeah, I did a reader survey and asked people, right, what what other sources they read, and mostly I was looking for reading recommendations. So what else do they consider similar? Overwhelmingly it was XKCD. Not so much—just because XKCD, it’s like if you have a little light that you're holding, a little candle you're holding up, and you're like, what does this remind you of? And like a lot of people are going to say the sun because they look up, and that’s where they see visible light.

KK: Sure.

BO: But I think in terms of actually similar writing, I think Toots of Unity is not so different, I think.

EL: Yeah. So I thought that was interesting because I have very few drawings on on mine. Although the ones that I do personally create are definitely bad. So I guess there’s that similarity.

BO: That’s the key thing, committing to the low quality.

KK: Yeah, but that's just it. I would argue they're actually not bad. So if I tried to draw like you draw, it would be worse. So I guess my book should just be Math with Worse Drawings.

BO: Right.

KK: You actually get a lot of emotion out of your characters, even though they're they're simple stick figures, right? There’s some skill there.

BO: Yeah, yeah. So I tried. I tried to draw them with a very expressive faces. Yeah, they're definitely still bad drawings is my feeling. Sometimes people say like, “Oh, but they've gotten so much better since you started the blog,” which is true, but it's one of these things where they could they could get a lot better every five-year interval for the next 50 years and still, I think not look like professional drawings by the end of it.

EL: Right. You're not approaching Rembrandt or anything.

KK: All right, so we asked you on here, because you do have bad drawings, but you also have thoughts about mathematics and you communicate them very well through your drawings. So you must have a favorite theorem. What is it?

BO: Yeah. So this one is drawn from my second book, actually, the second book is about calculus. And I have to confess I already kind of strayed from the assignment because it's not so much a favorite theorem as a favorite construction.

KK: Oh, that’s cool.

EL: You know, we get rule breakers on here. So yeah, it happens.

BO: Yeah, I guess that's the nature of mathematicians, they like to bend the rules and imagine new premises. So pretending that this were titled My Favorite cCnstruction, I would pick Weierstrass’s function. So that you know, first introduced in 1872. And the idea is it's this function which is continuous everywhere and differentiable nowhere.

EL: Yeah. Do you want to describe maybe what this looks like for anyone who might not have seen it yet?

BO: Yeah, sure. So when you're picturing a graph, right, you're probably picturing—it varies. I teach secondary school. So students are usually picturing a fairly small set of possibilities, right? Like you're picturing a line, maybe you're thinking of a parabola, maybe something with a few more squiggles, maybe as many squiggles as a sine wave going up and down. But they all have a few things in common one is that almost anything that students are going to picture is continuous everywhere. So basically, it's made of one unbroken line. You can imagine drawing it with your pencil without picking the pencil up. And then the other feature that they have is that they—this one's a little subtler, but there will be almost no points that are jagged, or sort of crooked, or, you know, if I picture an absolute value graph, right, it sort of is a straight line going down to the origin from the left, and then there's a sharp corner at the origin, and then it rises away from that sharp corner. And so those kind of sharp corners, you may have one or two in a graph a student would draw, but that's sort of it. You know, like sharp corners are weird. You don't can't draw all sharp corners. It feels like between any two sharp corners on your graph, there's going to have to be some some kind of non-sharp stuff connecting it, some kind of smooth bits going between them.

KK: Right.

BO: And so what sort of wild about about Weierstrass’s function is that you look at it, and it just looks very jagged. It’s got a lot of sharp corners. And you start zooming in, and you see that even between the sharp corners, there are more sharp corners. And you keep zooming in and there's just sharp corners all the way down. It's what we today call it fractal. Although back then that word wasn't around. And it's just it's the entire thing. Every single point along this curve is in some sense, a sharp corner.

EL: Yeah, it kind of looks like an absolute value everywhere.

BO: Yeah, exactly. It has that cusp at every single point you could look at.

KK: Right? So very pathological in nature. And, you know, I'm sure I've seen the construction of this. Is it easy to say what the construction is? Or is this going to be too technical for an audio format?

BO: It’s actually not hard to construct. There are there whole families of functions that have the same property. But Weierstrass’s is pretty simple. He starts with basically just a cosine curve. So you sort of have cosine of πx. So picture, you know, a cosine wave that has a period of two. And then you do another one that has a much shorter period. So you can sort of pick different numbers. But let's say the next one that you add on has a period that's 21 times faster. So it's sort of going up and down much quicker. And it's shorter, though, we've shrunk the amplitude also. So it's only about a third, let's say, as tall. And so you add that onto your first function. So now we've got—we started with just a nice, gentle wave. And now we've got a wave that has lots of little waves kind of coming off of it. And then you keep repeating that process. So the next, the second one in the iteration has a period of 21 cycles for two units. The next one has 212 cycles. And it's 1/9 the height of the original.

KK: Okay.

BO: And then after that, you're going to do you know, 213 cycles in the same span, 214 cycles. And so it goes—I don't know if you can hear my daughter is crying in the background, because I think she she finds it sort of upsetting to imagine the function that's has this kind of weird property.

EL: Fair.

BO: Especially because it's such a simple construction. Right? It's just, like, little building blocks for her that we're putting together. And one of the things I like about the construction, is it at no step, do you have any non-differentiable points, actually. It's a wave with a little wave on top of it and lots of little waves on top of that, and then tons and tons of little waves on top of that, but these are all smooth, nice, curving waves. And then it's only in the limit, sort of at the at the end of that infinite bridge, that suddenly it goes from all these little waves to its differentiable nowhere.

KK: I mean, I could see why that would be true, right?

BO: Yeah, right. Right. It feels like it's getting worse. And you can do—Weierstrass’s function is really a whole family of functions. He came up with some conditions that you need, basically that’s the basic idea. You need to pick an odd number for the number of cycles and then a geometric series for for the amplitude.

KK: So what's so appealing about this to you? It's just you can't draw it well, like you have to draw it badly?

KK: Yeah, that's one thing, right. Exactly. I try to push people into my corner, force them to have to drop badly. I do like that this is something—right, graphs of functions are so concrete. And yet this one you really can't draw. I've got it in my book, I have a picture of the first few iterations. And already, you can't tell the difference between the third step and the fourth step. So I had to, I had to, you know, do a little box and an inset picture and say, actually, in this fourth step, what looks like one little wave is really made up of 21 smaller waves. So I do sort of like that, how quickly we get into something kind of unimaginable and strange. And also, you know, I'm not a historian of mathematics. And so I always wind up feeling like I'm peddling sort of fairy tales about about mathematical history more than the complicated truth that is history. But the role that this function played in going from a world where it felt like functions were kind of nice and were something we had a handle on, into opening up this world where, like, oh no, there are all these pathological things going on out there. And there are just these monsters that lurk in the world of possibility.

KK: Yeah.

EL: Right. And was this it—Do you know, was this maybe one of the first, or the first step towards realizing that in some measure sense, like, all functions are completely pathological? Do you know kind of where it fell there, or, like, what the purpose was of creating it in the first place?

BO: Yeah, I think that's exactly right. I don't know the ins and outs of that story. I do know that, right, if you look in spaces of functions, that they sort of all have this property, right, among continuous functions, I think it's only a set of measure zero that doesn't have this property. So the sort of basic narrative as I understand it, leading from kind of the start of the 19th century to the end of the 19th century, is basically thinking that we can mostly assume things are good, to realizing that sometimes things are bad (like this function), culminating in the realization that actually basically everything is bad. And the good stuff is just these rare diamonds.

EL: Yeah, I guess maybe this slight, I don't know, silver lining, is that often we can approximate with good things instead. I don't know if that's like the next step on the evolution or something.

BO: Right. Yeah, I guess that's right. Certainly, that's a nice way to salvage some a silver lining, salvage a happy message. Because it's true, right? Even though, a simpler example, the rationals are only a set of measure zero and the reals, you know, they're everywhere, they're dense. So at least, you know, if you have some weird number, you can at least approximate it with a rational.

EL: Yeah, I was just thinking when you were saying this, how it has a really nice analogy to the rationals. And, and even algebraic numbers and stuff like, “Okay, start naming numbers,” you'll probably name whole numbers, which are, you know, this sparse set of measure zero. It’s like, o”h, be more creative,” like, “Okay, well, I'll name some fractions and some square roots and stuff.” But you're still just naming sets of measure zero, you’re never naming some weird transcendental function that I can't figure out a way to compute it.

BO: Yeah, it is funny, right? Because in some sense, right? We've imagined these things called numbers and these things called functions. And then you ask us to pick examples. And we pick the most unlikely, nicest hand-picked, cherry-picked examples. And so the actual stuff—we’ve imagined this category called functions, and most of what's in that category that we developed, we came up with that definition, most of what's in there is stuff that's much too weird for us to begin to picture.

EL: Yeah.

BO: Which says something about, I guess, our reach exceeding our grasp or something. I don't really know, but they are our definitions can really outrun our intuition.

EL: Yeah. So where did you first encounter this function?

BO: That’s a good question. I feel like probably as a kind of folklore bit in maybe 12th grade math. I feel like when I was probably first learning calculus, it was sort of whispered about. You know, my teacher sort of mentioned it offhand. And that was very enticing, and in some sense, that's actually where my whole second book comes from, is all these little bits of folklore, not exactly the thing you teach in class, but the little, I don't know, the thing that gets mentioned offhand. And you go “Wait, what, what was that?” “Oh, well, don't worry. You'll learn about that in your real analysis class in four years.” I don't want to learn about that in four years. Tell me about that now. I want to know about that weird function. And then I think the first proper reading I did was probably in a William Dunham’s book The Calculus Gallery, which is a nice book going through different bits of historical mathematics, beginning with the beginnings of calculus through through like the late 19th century. And he has the here's a nice discussion of the function and its construction.

KK: So when we were preparing for this, you also mentioned there are connections to Brownian motion here. Do you want to mention those for our audience?

BO: Yeah, I love that this turns out—so I have some quotes here from right when this function was sort of debuted, right when it was introduced to the world. You have Émile Picard, his line was, “If Newton and Leibniz had thought that continuous functions do not necessarily have a derivative, the differential calculus would never have been invented.” Which I like. If Newton and Leibniz knew what you were going to do to their legacy, they would never have done this! They would have rejected the whole premise. And then Charles Hermite? [Pronounced “her might, wonders if the pronunciation is correct]

KK: Hermite. [Pronounced “her meet”]

BO: That sounds better. Sounds good. Sure. Right. His line was, and I don't know what the context was, but, “I turn away with fright and horror from this lamentable evil of functions that do not have derivatives.” Which is really layering on I like the way people spoke in the 19th century. There was more, a lot more flavor to their their language.

EL: Yeah.

BO: And Poincaré also, he was saying 100 years ago prior to Weierstrass developing it, such a function would have been regarded as an outrage to common sense. Anyway, so I mention all those. You mentioned Brownian motion, right? The instinct when you see this function is that this is utterly pathological. This is math just completely losing touch with physical reality and giving us these weird intellectual puzzles and strange constructions that can't possibly mean anything to real human beings. And then it turns out that that's not true at all, that Brownian motion—so you look at pollen dancing around on the surface of some water, and it's jumping around in these really crazy aggressive ways. And it turns out our best models of that process, you know, of any kind of Brownian motions—you know, coal dust in the air or pollen on water—our best model to a pretty good approximation has the same property. The path is so jagged and surprising and full of jumps from moment to moment that it's nowhere differentiable, even though the particle obviously sort of has to be continuous. It can’t be discontinuous, I mean, it's jumping, like literally transporting from one place to another. So that's not really the right model. But it is non-differentiable everywhere, which means, weirdly, that it doesn't have a speed, right? Like, a derivative is a is a velocity.

EL: So that means maybe an average speed but not a speed at any time.

BO: Yeah, well, actually, even—I think it depends how you measure. I’d have to looked back at this, because what it means sort of between any two moments according to the model, between any two points in time, is traversing an infinite distance. So I guess it could have an average velocity, but the average speed I think winds up being infinite rates. Over a given time interval, you can just take how far it travels that time interval and divide by time, but I think the speed, if you take the absolute value of the magnitude? I think you sort of wind up with infinite speed, maybe? But really, it's just that you can’t—speed is no longer a meaningful notion. It's moving in such an erratic way. that n you can't even talk about speed.

KK: Well, because that tends to imply a direction. I mean, you know, it’s really velocity. That always struck me as that's the real problem, is that you can't figure out what direction it's going, because it's effectively moving randomly, right?

BO: Yeah, I think that's fair. Yeah. The only way I can build any intuition about it is to picture a single—imagine a baseball having a single non-differentiable moment. So like, you toss it up in the air. And usually what would happen is that it goes up in the air, it kind of slows down and slows down and slows down. There's that one moment when it's kind of not moving at all. And then it begins to fall. And so the non-differentiable version would be, like, you throw it up in the air, it's traveling up at 10 meters per second, and then a trillionth of a second later, it's traveling down at 10 meters per second. And what's happening at that moment? Well, it's just unimaginable. And now for Brownian motion, you've got to picture that that moment is every moment.

KK: Right. Yeah. Weird, weird world.

BO: Yeah.

KK: So another thing we like to do on this podcast is ask our guests to pair their, well in your case construction, with something. What does the Weierstrass function pair with?

BO: Yeah. So I think, I have two things in mind, both of them constructions of new things that kind of opened up new new possibilities that people could not have imagined before. So the first one, maybe I should have picked a specific dish, but I'm picturing basically just molecular gastronomy, this movement in in cooking where you take—one example I just saw recently in a book was, I think it was WD-50, a sort of famous molecular gastronomy restaurant in New York, where they had taken, the comes to you and it looks like a small, poppyseed bagel with lox. And then as it gets closer, you realize it's not a poppyseed bagel with lox, it's ice cream that looks almost identical to a poppyseed bagel with lox. So that's sort of weird enough already. And then you take a taste and you realize that actually, it tastes exactly like a poppyseed bagel with lox, because they've somehow worked in all the flavors into the ice cream.

KK: Hmm.

BO: Anyway, so molecular gastronomy basically is about imagining very, very weird possibilities of food that are outside our usual traditions, much in the way that Weierstrass’s function kind of steps outside the traditional structures of math.

EL: Yeah, I like this a lot. It's a good one. Partly because I'm a little bit of a foodie. And like, when I lived in Chicago, we went to this restaurant that had this amazing, like, molecular gastronomy thing. I’m trying to remember one of the things we had was this frozen sphere of blue cheese. And it was so weird and good. Yeah, you’d get you get like puffs of air that are something, and there’s, like, a ham sandwich, but it was like the bread was only the crust somehow there's like nothing inside. Yeah, it was all these weird things. Liquefied olive that was like in inside some little gelatin thing, and so it was just like concentrated olive taste that bursts in your mouth. So good.

BO: That sounds awesome to me the the molecular gastronomy food. I have very little experience of it firsthand.

KK: So you mentioned a second possible pairing. What would that be?

BO: Yeah, so the other one I had in mind is music. It's a Beatles album, Revolver.

KK: Great album.

BO: One of my favorite albums, and much like molecular gastronomy shows that the foods that we're eating are actually just a tiny subset of the possible foods that are out there, similarly what revolver did for for pop music and in ’65 whenever it came out.

KK: ’66.

BO: Okay. 66 Alright, thank you for that.

EL: I am not well-versed in albums of The Beatles. You know, I am familiar with the music of the Beatles, don’t worry. But I don't know what's on what album. So what is this album?

BO: So Kevin and I can probably go to track by track for you.

KK: I’d have to think about it, but it's got Norwegian Wood on it, for example.

BO: Oh, that's rubber sole, actually.

KK: Oh, that’s Rubber Soul. You're right. Yeah, I lost my Beatles cred. That's right. My bad. I mean, some would argue that—so Revolver was, some people argue, was the first album. Before that, albums had just been collections of singles, even in the case of the Beatles, but Revolver holds together as a piece.

BO: Yeah, that’s one thing. Which again, there's probably some an analogy to Weierstrass’s function there. Also, it begins with this kind of weird countdown where, I don’t remember if it's John or George, but they’re saying 1234 in the intro into Taxman.

KK: Yeah. Into Taxman, which is probably, it's not my favorite Beatles song, but it's certainly among the top four. Right.

BO: Yeah. So that one, already right there it’s a pop song about taxes, which is already, so lyrically, we're exploring different parts of the possibility space than musicians were before. Track two is Eleanor Rigby, which is, the only instrumentation is strings. Which again is something that you didn't really hear in pop. You know, Yesterday had brought in some strings, that was sort of innovative. Other bands have done similar things but, but the idea of a song that’s all strings, and then I’m Only Sleeping as the third track, which has this backwards guitar. They recorded the guitar and just played it backwards. And then Yellow Submarine, which is, like, this weird Raffi song that somehow snuck onto a Beatles album. Yeah, and then For No One has this beautiful French horn solo. Yes, every track is drawn from sort of a distant corner of this space of possible popular music, these kind of corners that had not been explored previously. Anyway, so my recommendation is, is think about the Weierstrass function while eating, you know, a giant sphere of blue cheese and listening to Taxman.

EL: Great. Yeah. I strongly urge all of our listeners to go do that right now.

BO: Yeah, if anyone does it, it'll probably be the first time that that set of activities has been done in conjunction.

EL: Yeah. But hopefully not the last.

BO: Hopefully not the last. That's right. Yeah. And most experiences are like that, in fact.

KK: So we also like to let our guests plug things. You clearly have things to plug.

BO: I do. Yeah. I'm a peddler of wares. Yes, so the prominent thing is my blog is Math with Bad Drawings, and you're welcome to come read that. I try to post funny, silly things there. And then my two books are Math with Bad Drawings, which kind of explores how math pops up in lots of different walks of life, like, you know, in thinking about lottery tickets or thinking about the Death Star is another chapter, and then Change Is the Only Constant is my second book, and it's all about calculus, and it’s sort of calculus through stories. Yeah, that one just came out earlier this year, and I'm quite proud of that one. So you should check it out.

KK: Yeah, so I own both of them. I've only read Math with Bad Drawings. I've been too busy so far to get to Change Is the Only Constant.

EL: And there were there been a slew of good pop—or I assume good because I haven't read most of them yet—pop math books that have come out recently, so yeah I feel like my stack is growing. It’s a fall of calculus or something.

BO: It’s been a banner year. And exactly, calculus has been really at the forefront. Steve Strogatz’s Infinite Powers was a New York Times bestseller, and then David Bressoud [Calculus Reordered] and others who I'm blanking on right now have had one. There was another graphic, like, cartoon calculus that came out earlier this year. So yeah, apparently calculus is kind of having a moment.

EL: Well, and I just saw one about curves.

KK: Curves for the Mathematically Curious. It's sitting on my desk. Many of these books that you've mentioned are sitting on my desk.

EL: So yeah, great year for reading about calculus, but I think Ben would prefer that you start that reading with Change Is the Only Constant.

BO: It's very frothy, it's very quick and light-hearted and should be—you can use it as your appetizer to get into the the, the cheesier balls of the later books.

KK: But it's highly non-trivial. I mean, you talk about really interesting stuff in these books. It's not some frothy thing. I mean it's lighthearted, but it's not simple.

BO: I appreciate that. Yeah, the early draft of the book I was doing pretty much a pretty faithful march through the AP Calculus curriculum. And then that draft wasn't really working. And I realized that part of what I wasn't doing that should be doing was since I'm not teaching, you know, you had to execute calculus maneuvers. I'm not teaching how to take derivatives. I can talk about anything as long as I can explain the ideas. So we've got Weierstrass’s function in there. And there's a little bit even on Lebesgue integration, and other sort of, some stuff on differential equations crops up. So since I'm not actually teaching a calculus course and I don't need to give tests on it, I just got to tell stories.

EL: Well, yeah, I hope people will check that out. And thanks for joining us today.

BO: Yeah, thanks so much for having me.

KK: Yeah. Thanks, Ben.

[outro]

Our guest on this episode, Ben Orlin, is a high school math teacher best-known for his blog and popular math books. He told us about Weierstrass’s construction of a function that is continuous everywhere but differentiable nowhere. Here is a short collection of links that might be interesting.

Ben’s Blog, Math with Bad Drawings

Math with Bad Drawings, the book

Change is the Only Constant

Episode 51 - Carina Curto

Evelyn Lamb: Hello, and welcome to My Favorite Theorem, the math theorem with no test at the end. I think I decided I liked that tagline. [Editor’s note: Nope, she really didn’t notice that slip of the tongue!]

Kevin Knudson: Okay.

EL: So we’re going to go with that. Yeah. I'm one of your hosts, Evelyn Lamb. I'm a freelance math and science writer in Salt Lake City, Utah. And this is the other host.

KK: I’m Kevin Knudson, a professor of mathematics at the University of Florida. How are you doing?

EL: I’m doing well. Yeah, not not anything too exciting going on here. My mother-in-law is coming to visit later today. So the fact that I have to record this podcast means my husband has to do the cleaning up to get ready.

KK: Wouldn’t he do that anyway? Since it’s his mom?

EL: Yeah, probably most of it. But now I've got a really good excuse.

KK: Yeah, sure. Well, Ellen and I had our 27th anniversary yesterday.

EL: Oh, congratulations.

KK: Yeah, we had a nice night out on the town. Got a hotel room just to sit around and watch hockey, as it turns out.

EL: Okay.

KK: But there's a pool at the hotel. And you know, it's hot in Florida, and we don't have a pool. And this is absurd—which Ellen reminds me of every day, that we need a pool—and I just keep telling her that we can either send the kid to college or have a pool. Okay.

EL: Yeah.

KK: I mean, I don't know. Anyway, we're not here talking about that, we're talking about math..

EL: Yes. And we're very excited today to have Carina Curto on the show. Hi, Carina, can you tell us a little bit about yourself?

Carina Curto: Hi, I'm Carina, and I'm a professor of mathematics at Penn State.

EL: Yeah, and I think I first—I don't think we've actually met. But I think the first time I saw you was at the Joint Meetings a few years ago. You gave a really interesting talk about, like, the topology of neural networks, and how your brain has these, like, basically kind of mental maps of spaces that you interact with. It was really cool. So is that the kind of research you do?

CC: Yeah, so that was—I remember that talk, actually, at the Joint Meetings in Seattle. So that was a talk about the uses of typology for understanding neural codes. And a lot of my research has been about that. And basically, everything I do is motivated in some way by questions in neuroscience. And so that was an example of work that's been motivated by neuroscience questions about how your brain encodes geometry and topology of space.

KK: Now, there's been a lot of a lot of TDA [topological data analysis] moving in that direction these last few years. People have been finding interesting uses of topology in neuroscience and studying the brain and imaging stuff like that, very cool stuff.

CC: Yeah.

EL: And did you come from more of a neuroscience background? Or have you been kind of picking that up as you go, coming from a math background?

CC: So I originally came from a mathematical physics background.

EL: Okay.

CC: I was actually a physics major as an undergrad. But I did a lot of math, so I was effectively a double major. And then I wanted to be a string theorist.

KK: Sure, yeah.

CC: I started grad school in 2000. So this is, like, right after Brian Greene’s The Elegant Universe came out.

EL: Right. Yeah.

CC: You know, I was young and impressionable. And so I kind of went that route because I loved physics, and I loved math. And it was kind of an area of physics that was using a lot of deep math. And so I went to grad school to do mathematical string theory in the math department at Duke. And I worked on Calabi-Yaus and, you know, extra dimensions and this kind of stuff. And it was, the math was mainly algebraic geometry, is what right HD thesis was in So this had nothing to do with neuroscience.

EL: Right.

CC: Nothing. And so basically about halfway through grad school—I don't know how better to put it, then I got a little disillusioned with string theory. People laugh now when I say that because everybody is.

KK: Sure.

CC: But I started kind of looking for other—I always wanted to do applied things, interdisciplinary things. And so neuroscience just seemed really exciting. I kind of discovered it randomly and started learning a lot about it and became fascinated. And so then when I finished my PhD, I actually took a postdoc in a neuroscience lab that had rats and, you know, was reporting from the cortex and all this stuff, because I just wanted to to learn as much neuroscience as possible. So I spent three years working in a lab. I didn't actually do experiments. I did mostly computational work and data analysis. But it was kind of a total cultural immersion sort of experience, coming from more of a pure math and physics background.

EL: Right. Yeah, I bet that was a really different experience

CC: It was really different. So I kind of left math in a sense for my first postdoc, and then I came back. So I did a second postdoc at Courant at NYU, and then started getting ideas of how I could tackle some questions in neuroscience using mathematics. And so ever since then, I've basically become a mathematical neuroscientist. I guess I would call myself.

KK: So 2/3 of this podcast is Duke alums. That's good.

CC: Oh yeah? Are you a Duke alum?

KK: I did my degree there too. I finished in ’96.

CC: Oh, yeah.

KK: Okay. Yeah.

CC: Cool.

EL: Nice. Well, so what is your favorite theorem?

CC: So I have many, but the one I chose for today is the Perron-Frobenius theorem.

KK: Nice.

EL: All right.

CC: And so you want to know about it, I guess?

KK: We do. So do our listeners.

CC: So it's actually really old. I mean, there are older theorems, but Perron proved it, I think in 1907 and Frobenius in 1912, so it carries both of their names. So it's over 100 years old. And it's a theorem and linear algebra. So it has to do with eigenvectors and eigenvalues of matrices.

KK: Okay.

CC: And so I'll just tell you quickly what it is. So, if you have a square matrix, so like an n×n square matrix with all positive—so there are many variations of that theorem. I'm going to tell you the simplest one—So if all the entries of your matrix are positive, then you are guaranteed that your largest eigenvalue is unique and real and is positive, so a positive real part. So eigenvalues can be complex. They can come in complex conjugate pairs, for example, but when we talk about the largest one, we mean the one that has the largest real part.

EL: Okay.

KK: All right.

CC: And so one part of the theorem is that that eigenvalue is unique and real and positive. And the other part is that you can pick the corresponding eigenvector for it to be all positive as well.

EL: Okay. And we were talking before we started taping that I'm not actually remembering for sure whether we've used the words eigenvector and eigenvalue yet on the podcast, which, I feel like we must have because we've done so many episodes, but yeah, can we maybe just say what those are for anyone who isn't familiar?

CC: Yeah. So when you have a matrix, like a square matrix, you have these special vectors. So the matrix operates on vectors. And so a lot of people have learned how to multiply a matrix by a vector. And so when you have a vector, so say your matrix is A and your vector is x, if A times x gives you a multiple of x back—so you basically keep the same vector, but maybe scale it—then x is called an eigenvector of A. And the scaling factor, which is often denoted λ, is called the eigenvalue associated to that eigenvector.

KK: Right. And you want x to be a nonzero vector in this situation.

CC: Yes, you want x to be nonzero, yes, otherwise it's trivial. And so I like to think about eigenvectors geometrically because if you think of your matrix operating on vectors in some Euclidean space, for example, then what it does, what the matrix will do, is it will pick up a vector and then move it to some other vector, right? So there's an operation that takes vectors to vectors, called linear transformations, that are manifested by the matrix multiplication. And so when you have an eigenvector, the matrix keeps the eigenvector on its own line and just scales, or it can flip the sign. If the eigenvalue is negative, it can flip it to point the other direction, but it basically preserves that line, which is called the eigenspace associated. So it has a nice geometric interpretation.

EL: Yeah. So the Perron-Frobeius theorem, then, says that if your matrix only has positive entries, then there's some eigenvector that's stretched by a positive amount.

CC: So yeah, so it says there's some eigenvector where the entries of the vector itself are all positive, right, so it lies in the positive orthant of your space, and also that the the corresponding eigenvalue is actually the largest in terms of absolute value. And the reason this is relevant is because there are many kind of dynamic processes that you can model by iterating a matrix multiplication. So, you know, one simple example is things like Markov chains. So if you have, say, different populations of something, whether it be, say, animals in an ecosystem or something, then you can have these transition matrices that will update the population. And so, if you have a situation where if your matrix that's updating your population has—whatever the leading eigenvalue is of that matrix is going to control somehow the long-term behavior of the population. So that top eigenvalue, that one with the largest absolute value, is really controlling the long-term behavior of your dynamic process.

EL: Right, it kind of dominates.

CC: It is dominating, right. And you can even see that just by hand when you sort of multiply, if you take a matrix times a vector, and then do it again, and then do it again. So instead of having A times x, you have A squared times x or A cubed times x. So it's like doing multiple iterations of this dynamic process. And you can see how, then, what’s going to happen to the to the vector if it's the eigenvector. Well, if it's an eigenvector, well, what's going to happen is when you apply the matrix once, A times x, you're going to get λ times x. Now apply A again. So now you're applying A to the quantity λx, but the λ comes out, by the linearity of the of the matrix multiplication, and then you have Ax again, so you get another factor of λ, so you get λ^2 times x. And so if you keep doing this, you see that if I do A^k times x, I get λ^k times x. And so if that λ is something, you know, bigger than 1, right, my process is going to blow up on me. And if it's less than 1, it's going to converge to zero as I keep taking powers. And so anyway, the point is that that top eigenvector is really going to dominate the dynamics and the behavior. And so it's really important if it's positive, and also if it's bigger or less than 1, and the Perron-Frobenius theorem basically tells you that you have, it gives you control over what that top eigenvalue looks like and moreover, associates it to an all-positive eigenvector, which is then a reflection of maybe the distribution of population. So it's important that that be positive too because lots of things we want to model our positive, like populations of things.

KK: Negative populations aren't good. Yeah,

CC: Yes, exactly. And so this is one of the reasons it's so, useful is because a lot of the things we want to model are—that vector that we apply the matrix to is reflecting something like populations, right?

KK: So already this is a very non-obvious statement, right? Because if I hand you an arbitrary matrix, I mean, even like a 2×2 rotation matrix, it doesn't have any eigenvalues, any real eigenvalues. But the entries aren't all positive, so you’re okay.

CC: Right. Exactly.

KK: But yeah, so a priori, it's not obvious that if I just hand you an n×n matrix with all real entries that it even has a real eigenvalue, period.

CC: Yeah. It's not obvious at all, and let alone that it's positive, and let alone that it has an eigenvector that's all positive. That's right. And the positivity of that eigenvector is really important, too.

EL: Yeah. So it seems like if you're doing some population model, just make sure your matrix has all positive entries. It’ll make your life a lot easier.

CC: So there's an interesting, so do you do you know what the most famous application of the Perron-Frobenius theorem is?

EL: I don't think I do.

KK: I might, but go ahead.

CC: You might, but I’ll go ahead?

KK: Can I guess?

CC: Sure.

KK: Is it Google?

CC: Yes. Good. Did you Google it ahead of time?

KK: No, this is sort of in the dark recesses of my memory that essentially they computed this eigenvector of the web graph.

CC: Right. Exactly. So back in the day, in the late ‘90s, when Larry Page and Sergey Brin came up with their original strategy for ranking web pages, they used this theorem. This is like, the original PageRank algorithm is based on this theorem, because they're, they have again the Markov process where they imagine some web—some animal or some person—crawling across the web. And so you have this graph of websites and edges between them. And you can model the random walk across the web as one of these Markov processes where there's some matrix that that reflects the connections between web pages that you apply over and over again to update the position of the of the web crawler. And and so now if you imagine a distribution of web crawlers, and you want to find out in the long run what pages do they end up on, or what fraction of web crawlers end up on which pages, it turns out that the Perron-Frobenius theorem gives you precisely the existence of this all-positive eigenvector, which is a positive probability that you have on every website for ending up there. And so if you look at the eigenvector itself, that you get from your web matrix, that will give you a ranking of web pages. So the biggest value will correspond to the most, you know, trafficked website. And smaller values will correspond to less popular websites, as predicted by this random walk model.

EL: Huh.

CC: And so it really is the basis of the original PageRank. I mean, they do fancier things now, and I'm sure they don't reveal it. But the original PageRank algorithm was really based on this. And this is the key theorem. So I think it's a it's kind of a fun thing. When I teach linear algebra, I always tell students about this.

KK: Linear Algebra can make you billions of dollars.

CC: Yes.

KK: That’ll catch students’ attention.

CC: Yes, it gets students’ attention.

EL: Yes. So where did you first encounter the Perron-Frobenius theorem?

CC: Probably in an undergrad linear algebra class, to be honest. But I also encountered it many more times. So I remember seeing it in more advanced math classes as a linear algebra fact that becomes useful a lot. And now that I'm a math biologist, I see it all the time because it's used in so many biological applications. And so I told you about a population biology application before, but it also comes up a lot in neural network theory that I do. So in my own research, I study these competitive neural networks. And here I have matrices of interactions that are actually all negative. But I can still apply the theorem. I can just flip the sign.

EL: Oh, right.

CC: And apply the theorem, and I still get this, you know, dominant eigenvalue and eigenvector. But in that case, the eigenvalue is actually negative, and I still have this all-positive eigenvector that I can choose. And that's actually important for proving certain results about the behavior of the neural networks that I study. So it's a theorem I actually use in my research.

EL: Yeah. So would you say that your appreciation of it has grown since you first saw it?

CC: Oh for sure. Because now I see it everywhere.

EL: Right.

CC: It was one of those fun facts, and now it’s in, you know, so many math things that I encounter. It's like, oh, they're using the Perron-Frobenius theorem. And it makes me happy.

EL: Yeah, well, when I first read the statement of the theorem, it's not like it bowled me over, like, “Oh, this is clearly going to be so useful everywhere.” So probably, as you see how many places it shows up, your appreciation grows.

CC: Yeah, I mean, that's one of the things that I think is really interesting about the theorem, because, I mean, many things in math are like this. But you know, surely when Perron and Frobenius proved it over 100 years ago, they never imagined what kinds of applications it would have. You know, they didn't imagine Google ranking web pages, or the neural network theory, or anything like this. And so it's one of these things where it's like, it's so basic. Maybe it could look initially like a boring fact of linear algebra, right? If you're just a student in a class and you're like, “Okay, there's going to be some eigenvector, eigenvalue, and it's positive, whatever.” And you can imagine just sort of brushing it off as another boring fact about matrices that you have to memorize for the test, right? And yet, it's surprisingly useful. I mean, it has applications in so many fields of applied math and in pure math, and so it's just one of those things that gives you respect for even seemingly simple and not obviously, it doesn't bowl you over, right, you can see the statement and you're not like, “Wow, that's so powerful!” But it ends up that it's actually the key thing you need in so many applications. And so, you know, it's earned its place over time. It's aged nicely.

EL: And do you have a favorite proof of this theorem?

CC: I mean, I like the elementary proofs. I mean, there are lots of proofs. So I think there's an interesting proof by Birkhoff. There are some proofs that involve the Brouwer fixed point theorem, which is something maybe somebody has chosen already.

EL: Yes, actually. Two people have chosen it!

CC: Two people have chosen the Brouwer fixed point theorem. Yeah, I would imagine that's a popular choice. So, yeah, there are some proofs that rely on that, which I think is kind of cool. So those are more modern proofs of it. That's the other thing I like about it, is that it has kind of old-school elementary proofs that an undergrad in a linear algebra class could understand. And then it also has these more modern proofs. And so it's kind of an interesting theorem in terms of the variety of proofs that it admits.

KK: So one of the things we like to do on this podcast is we like to invite our guests to pair their theorem with something. So I'm curious, I have to know what pairs well with the Perron-Frobenius theorem?

CC: I was so stressed out about this pairing thing!

KK: This is not unusual. Everybody says this. Yeah.

CC: What is this?

KK: It’s the fun part of the show!

CC: I know, I know. And so don't know if this is a good pairing, but I came up with this. So I went to play tennis yesterday. And I was playing doubles with some friends of mine. And I told them, I was like, I have to come up with a pairing for my favorite theorem. So we chatted about it for a while. And as I was playing, I decided that I will pair it with my favorite tennis shot.

EL: Okay.

CC: So, my favorite shot in tennis is a backhand down the line.

KK: Yes.

CC: Yeah?

KK: I never could master that!

CC: Yeah. The backhand down the line is one of the basic ground strokes. But it's maybe the hardest one for amateur players to master. I mean, the pros all do it well. But, you know, for amateurs, it's kind of hard. So usually people hit their backhand cross court. But if you can hit that backhand down the line, especially when someone's at the net, like in doubles, and you pass them, it's just very satisfying, kind of like, win the point. And for my tennis game, when my backhand down the line is on, that's when I'm playing really well.

EL: Nice.

CC: And I like the linearity of it.

EL: Right, it does seem like, you know, you're pushing it down.

CC: Like I'm pushing that eigenvector.

KK: It’s very positive, everything's positive about it.

CC: Everything’s positive. The vector with the tennis ball, just exploding down the line. It's sort of maybe it's a stretch, but that's kind of what I decided.

EL: A…stretch? Like with an eigenvalue and eigenvector?

CC: Right, exactly. I needed to find a pairing that was a stretch.

EL: I think this is a really great pairing. And you know, something I love about the pairing thing that we do—other than the fact that I came up with it, so of course, I'm absurdly proud of it—is that I think, for me at least it's built all these bizarre connections with math and other things. It's like, now when I see the mean value theorem, I'm like, “Oh, I could eat a mango.” Or like, all these weird things. So now when I see people playing tennis, I'll be like, “Oh, the Perron-Frobenius theorem.”

CC: Of course.

EL: So are you a pretty serious tennis player?

CC: I mean, not anymore. I played in college for a little bit. So when I was a junior, I was pretty serious.

EL: Nice. Yeah, I’m not really a tennis person I've never played or really followed it. But I guess there's like some tennis going on right now that's important?

CC: The French Open?

EL: That’s the one!

KK: Nadal really stuck it to Federer this morning. I played obsessively in high school, and I was never really any good, and then I kind of gave it up for a long time, and I picked up again in my 30s and did league tennis when I lived in Mississippi. And my team at our level—we were just sort of very intermediate players, you know—we won the state championship two years in a row.

CC: Wow.

KK: And then and then I gave it up again when I moved to Florida. My shoulder can't take it anymore. I was one of these guys with a big booming serve and a pretty good forehand and then nothing else, right?

CC: Yeah.

KK: So you know, if you work my backhand enough you're going to destroy me.

EL: Nice. Oh, yeah, that's a that's a lot of fun. And I hope other our tennis appreciator listeners will now have have an extra reason to enjoy this theorem too. So yeah, we also like to give our guests a chance, like if they have a website or book or anything they want to mention—you know, if people want to find them online and chat about tennis or linear algebra— is there anything you want to mention?

CC: I mean, I don't have a book or anything that I can plug, but I guess I wanted to just plug linear algebra as a subject.

KK: Sure.

CC: I feel like linear algebra is one of the grand achievements of humanity in some ways. And it should really shine in the public consciousness at the same level as calculus, I think.

EL: Yeah.

KK: Maybe even more.

CC: Yeah, maybe even more. And now, everybody knows about calculus. Every little kid knows about calculus. Everyone is like, “Oh, when when are you going to get to calculus?” You know, calculus, calculus. And linear algebra—it also has kind of a weird name, right, so it sounds very elementary somehow, linear and algebra—but it's such a powerful subject. And it's very basic, like calculus, and it's used widely and so I just want to plug linear algebra.

EL: Right. I sometimes feel like there are basically—so math can boil down to like, doing integration by parts really well or doing linear algebra really. Like, I joked with somebody, like, I didn't end up doing a PhD in a field that used a lot of linear algebra, but I sort of got my PhD in applied integration by parts, it's just like, “Oh, yeah. Figure out an estimate based on doing this.” And I think linear algebra, especially now with how important social media and the internet are, it is really an important field that, I agree, more people should know about. It is one of the classes that when I took it in college, it's one of the reasons I—at that time, I was trying to get enough credits to finish my math minor. And I was like, “Oh, yeah, actually, this is pretty cool. Maybe I should learn a little more of this math stuff.” So, yeah, great class.

CC: And you know, it's everywhere. And you know, there are all these people, almost more people have heard of algebraic topology than linear algebra, outside, you know, because it's this fancy topology or whatever. But when it comes down to it, it's all linear algebra tricks. With some vision of how to package them together, of course, I’m not trying to diminish the field, but somehow linear algebra doesn't get it’s—it’s the workhorse behind so much cool math and yeah, doesn't get its due.

EL: Yes, definitely agree.

KK: Yeah. All right. Well, here's to linear algebra.

EL: Thanks a lot for joining us.

CC: Thank you.

KK: It was fun.

[outro]

Our guest on this episode, Carina Curto, is a mathematician at Penn State University who specializes in applications in biology and neuroscience. She talked about the Perron-Frobenius theorem. Here are some links you may find useful as you listen to this episode.

Curto’s website
A short video of Curto talking about how her background in math and physics is useful in neuroscience and a longer interview in Quanta Magazine
An article version of Curto’s talk a few years ago about topology and the neural code
Curto ended the episode with a plug for linear algebra as a whole. If you’re looking for an engaging video introduction to the subject, check out this playlist from 3blue1brown.

Episode 50 - aBa

Evelyn Lamb: Hello, and welcome to My Favorite Theorem, a math podcast. I'm one of your hosts, Evelyn Lamb. I'm a freelance math and science writer, usually in Salt Lake City, Utah, currently in Providence, Rhode Island. And this is your other host.

Kevin Knudson: Hi. I’m Kevin Knudson, professor of mathematics, almost always at the University of Florida these days. How's it going?

EL: All right. We had hours of torrential rain last night, which is something that just doesn't happen a whole lot in Utah but happens a little more often in Providence. So I got to go to sleep listening to that, which always feels so cozy, to be inside when it's pouring outside.

KK: Yeah, well, it's actually finally pleasant in Florida. Really very nice today and the sun's out, although it's gotten chilly—people can't see me doing the air quotes—it’s gotten “chilly.” So the bugs are trying to come into the house. So the other night we were sitting there watching something on Netflix and my wife feels this little tickle on her leg and it was one of those big flying, you know, Florida roaches that we have here.

EL: Ooh

KK: And our dog just stood there wagging at her like, “This is fun.” You know?

EL: A new friend!

KK: “Why did you scream?”

EL: Yeah, well, we’re happy today to invite aBa to the show. ABa, would you like to introduce yourself?

aBa Mbirika: Oh, hello. I’m aBa. I'm here in Wisconsin at the University of Wisconsin Eau Claire. And I have been here teaching now for six years. I tell them where I'm from?

EL: Yeah.

KK: Sure.

aM: Okay. I am from, I was born and raised in New York City. I prefer never to go back there. And then I moved to San Francisco, lived there for a while. Prefer never to go back there. And then I went up to Sonoma County to do some college and then moved to Iowa, and Iowa is really what I call home. I'm not a city guy anymore. Like Iowa is definitely my home.

EL: Okay.

KK: So Southwestern Wisconsin is also okay?

aM: Yeah, it's very relaxing. I feel like I'm in a very small town. I just ride my bicycle. I still don't know how to drive, like all my friends from New York and San Francisco. But I don't need a car here. There's nowhere to go.

EL: Yeah.

aM: But can I address why you just called me aBa, as I asked you to?

EL: Yeah.

aM: Yeah, because maybe I'll just put this on the record. I mean, I don't use my last name. I think the last time I actually said some version of my last name was grad school, maybe? The year 2008 or something, like 10 years ago was the last time anyone's ever heard it said. And part of the issue is that it's It's pronounced different depending on who's saying it in my family. And actually it's spelled different depending on who’s in the family. Sometimes they have different letters. Sometimes there's no R. Sometimes it’s—so in any case, if I start to say one pronunciation, I know Americans are going to go to town and say this is the pronunciation. And that's not the case. I can't ask my dad. He's passed now, but he didn’t have a favorite. He said it five different ways my whole life, depending on context. So he doesn't have a preference, and I'm not going to impose one. So I'm just aBa, and I'm okay with that.

EL: Yeah, well, and as far as I know, you're currently the only mathematician named aBa. Or at least spelled the way yours is spelled.

aM: Oh yeah, in the arXiv. Yeah, on Mathscinet that it’s. Yeah, I'm the only one there. Recently someone invited me to a wedding and they were like, what's your address? And I said, “aBa and my address is definitely enough.”

EL: Yeah, so what theorem would you like to tell us about?

aM: Oh, okay, well I was listening actually to a couple of you shows recently, and Holly didn’t have a favorite theorem, Holly Krieger. I'm exactly the same way. I don't even have a theorem of, like, the week. She was lucky to have that. I have a theorem of the moment. I would like to talk about something I discovered when I was in college, that’s kind of the reason. but can I briefly say some of my like, top hits just because?

EL: Oh yeah.

KK: We love top 10 lists. Yeah, please.

aM: Okay. So I'm in combinatorics, loosely defined, but I have no reason—I don't know why people throw me in that bubble. But that's the bubble that that I've been thrown in. But my thesis—actually, I don’t ever remember the title, so I have to read it off a piece of paper—Analysis of symmetric function ideals towards a combinatorial description of the cohomology ring of Hessenberg varieties.

KK: Okay.

aM: Okay, all those words are necessary there. But my advisor said, “You're in combinatorics.” Essentially, my problem was, we were studying an object and algebraic geometry, this thing called a Hessenberg variety. To study this thing we used topology. We looked at the cohomology ring of this, but that was very difficult. So we looked at this graded ring from the lens of commutative algebra. And I studied the algebra the string by looking at symmetric functions, ideals of symmetric functions, and hence that's where my advisor said, “You're in combinatorics.” So it was the main tool used to study a problem an algebraic geometry that we looked at topology. Whatever, so I don't know what I am. But any case for top 10 hits, not top 10, but diagram chasing. Love it. Love it.

EL: Wow, I really don't share that love, but I’m glad somebody does love it.

aM: Oh, it's just so fun for students.

KK: So the snake lemma, right?

aM: The snake lemma, yes. It's a little bit maybe above the level of our algebra two class that I teach here for undergrads, but of course I snuck it in anyways. And the short five lemma. Those are like, would be my favorites if the moment was, like, months ago. In number theory I have too many faves, but I’m going to limit it to Euler-Fermat’s theorem that if a and n are coprime, then a to the power of the Euler totient function of n is congruent to 1 mod n. But that leads to Gauss’s epically cool awesome theorem on the existence of primitive roots. Now, this is my current craze.

EL: Okay.

aM: And this is just looking at the group of units in Z mod nZ, or more simply the multiplicative group of units of integers modulo n. When is this group cyclic? And Gauss said it's only cyclic when n is the numbers 2, or 4, or an odd prime to a k power, or twice an odd prime to some k-th power. And basically, those are very few. I mean, those are very little numbers in the broad spectrum of the infinity of the natural numbers. So this is very cool. In fact, I'm doing a non-class right now with a professor who retired maybe 10 years ago from our university, and I emailed him and said, “Want to have fun on my like my research day off?” And we’re studying primitive roots because I don't know anything about it. Like, my favorite things are things I know nothing about and I want to learn a lot about.

EL: Yeah, I don't think I've heard that theorem before. So yeah, I'll have to look that up later.

aM: Yes. And then the last one is from analysis, and I did hear Adrianna Salerno talked about it and in fact, I think also someone before her on your podcast, but Cantor’s theorem on uncountability of the real numbers.

EL: Yeah, that's that's a real classic.

aM: I just taught that two days ago in analysis, and like, it's like waiting for their heads to explode. And I think, I don't know, my students’ heads weren't all exploding. But I was like, “This is so exciting! Why are you not feeling the excitement?” So yeah, yeah, it was only my second time teaching analysis. So maybe I have to work on my sell.

EL: Yeah, you'll get them next time.

aM: Yeah. It's so cool! I even mentioned it to my class that’s non-math majors, just looking at sets, basic set theory. And this is my non-math class. These students hate math. They're scared of math. And I say, “You know, the infinity you know, it's kind of small. I mean, you're not going to be tested on this ever. But can I please take five minutes to like, share something wonderful?” So I gave them the baby version of Cantor’s theorem. Yeah, but that's it. I just want to throw those out there before I was forced to give you my favorite theorem.

EL: Yes. So now…

KK: We are going to force you, aBa. What is your favorite theorem?

EL: We had the prelude, so now this is the main event.

aM: Okay, main event time. Okay, you were all young once, and you remember—oh, we’re all young, all the time, sorry—but divisibility by 9. I guess when we're in high school—maybe even before that—we know that the number 108 is divisible by 9 because 1+0+8 is equal to 9. And that's divisible by 9. And 81 is divisible by 9 because 8+1 is 9, and 9 is divisible by 9. But not just that, the number 1818 is divisible by 9 because 1+8+1+8 is 18. And that's divisible by 9. So when we add up the digits of a number, and if that sum is divisible by 9, then the number itself is divisible by 9. And students know this. I mean, everyone kind of knows that this is true. I guess I was a sophomore in college. That was maybe a good 4 to 6 years after I started college because, well, that was hard. It's a different podcast altogether, but I made some choices to meet friends who made it really hard for me to go to school consistently in San Francisco—part of the reason why I'm kind of okay not going back there much anymore. Friends got into trouble too much.

But I took a number theory course and learned a proof for that. And the proof just blew my mind because it was very simple. And I wasn't a full-blown math major yet. I think I was in physics— I had eight majors, different majors through the time—I wasn't a math person yet. And I was on a bus going from—Oh, this is in Sonoma County. I went to Sonoma State University as my fourth or fifth college that I was trying to have a stable environment in. And this one worked. I graduated from there in 2004. It definitely worked. So I was on a bus to visit some of my bad friends in San Francisco—who I love, by the way, I'm just saying of the bad habits—and I was thinking about this theorem of divisibility by 9 and saying, what about divisibility by 7? No one talks about that. Like, we had learned divisibility by 11. Like the alternating sum of the digits, if that's divisible by 11, then the number is divisible by 11. But what about 7? You know, is that doable? Or why is it not talked about?

EL: Yeah.

aM: So it was an hour and a half bus ride. And I figured it out. And it was extremely, like, the same exact proof as the divisibility by 9, but boiled down to one tiny little change. But it's not so much that I love this theorem. I actually haven't even told it to you yet. But that I did the proof, that it changed my life. I really—that’s the only thing I can go back to and say why am I an associate professor at a university in Wisconsin right now. It was the life-changing event. So let me tell you the theorem.

EL: Yeah.

aM: It’s hardly a theorem, and this is why I don't know if it even belongs on this show.

EL: Oh, it totally does!

aM: Okay, so I don't even think I had calc 2 yet when I discovered this little theorem. All right, so here we go. So look at the decimal representation of some natural number. Call it n.

EL: I’ve got my pencil out. I'm writing this down.

aM: Oh, okay. Oh, great. Okay, I'm reading off a piece of paper that I wrote down.

EL: Yeah, you said something about it to us earlier. And I was like, “I'm going to need to have this written down.” It’s funny that I do a podcast because I really like looking at things that are written down. That helps me a lot. But let's podcast this thing.

aM: Okay, so say we have a number with k+1 digits. And so I'm saying k+1 because I want to enumerate the digits as follows: the units digit I'm going to call a0, the tens digit I’ll call a1 the hundreds place digit a2 etc, etc, down to the k+1st digit, which we’ll call ak. So read right to left, like in Hebrew, a0, a1 a2 … (or \cdots, you LaTeX people) ak-1 then the last far left digit ak.

EL: Yeah.

aM: So that is a decimal representation of a number. I mean, we're just, you know, like number 1008. That would be a0 is the number 8, a1 is the number 0, a2 is number 0, a3 is the number 1. So we just read right to left. So we can represent this number, and everybody knows this when you're in junior math, I guess in elementary school, that we can write the number—now I'm using a pen—123 as 3 times 1 plus—how many tens do we have? Well, we have two tens. So 2 times 10. How many hundreds do we have? Well, we have one of those. So 1 times 100. So just talking about, yeah, this is mathematics of the place value system in base 10. No surprise here. But a nicer way to write it as a fat sum, where i, the index goes from 0 to k of ai times 10i.

EL: Yeah.

aM: That’s how we in our little family of math nerds, how we compactly write that. So when we think about when does this number divisible by 7? It suffices to think about when what is the remainder when each of these summands is—when we divide each of these summands by 7, and then add up all those remainders and then take that modulo 7. So the key and crux of this argument is that what is 10 congruent to mod 7? Well, 10 leaves the remainder of 3 when you divide by 7. In the great language of concurrences—Thank you, Gauss—10≡3 mod 7. So now we can look at this, all of these tens we have. We have a0 ×100+ a1 ×101 + a2 ×102, etc, etc. When we divide this by 7, this number really is now a0 ×30 — because I can replace my 100 with 30 —plus a1 ×31 instead of—because 101 is the same as 31 in modulo 7 land—plus a2 ×32, etc. etc…. to the last one, ak ×3k. Okay, here I am on the bus thinking, “This is only cool if I know all my powers of 3.”

EL: Yeah. Which are not really that much easier than figuring it out in the first place.

aM: Okay, but I'm young mathematically and I'm just really super excited. So one little example, I guess this is not, I can't remember what I did on the bus, but 1008 is is a number that's divisible by seven. And let's just perform this check, using this check on this number. So is 1008 really divisible by 7? What we can do is according to this, I take the far right digit, the units digit, and that's 8 ×30, so that's just the number 8, 8×1, plus 0×31. Well, that's just 0, thankfully. Then the next, the hundreds place, that’s 0×32. So that's just another 0. And then lastly, the thousands place, 1×33 and that's 27. Add up now my numbers 8+0+0+27. And that's 35. And that's easy to know that the divisibility of. 7 divides 35 and thus 7 divides 1008. And, yeah, I don't know, I’m traveling back in time, and this is not a marvelous thing. But everybody, unfortunately, who I saw in San Francisco that day, and the next day, learned this. I just had to teach all my friends because I was like, “Well, this is not what I'm doing for college. This is something I figured out on the bus. This math stuff is great.”

EL: Yeah, just the fact that you got to own that.

aM: Yeah. And that also it wasn't in the book, and actually it wasn't in subsequently any book I've ever looked in ever since. But it's still just cute. I mean, it's available. And what it did, I guess it just touched me in a way, where I guess I didn't know about research, I didn't know about a PhD program. My end goal was to get a job, continue at the photocopy place that was near the college, where I worked. I really told my boss that, and I really believed that I was going to do that. And our school never really sent people to graduate programs. I was one of the first. And I don't know, it just changed me. And there were a lot of troubles in my life before then. And this is something that I owned. And that's my favorite theorem on that bus that day.

KK: It’s kind of an origin story, right?

aM: Yes, because people ask me, how did you get interested in math? And I always say the classic thing. Forget this story, but I'm also not speaking to math people. My usual thing is the rave scene. I mean, that was what I was involved in in San Francisco, and then, I don't know if you know what that is, but electronic dance music parties that happen in beaches and fields and farms and houses.

EL: What, you don’t think we go to a lot of raves?

aM: I don’t know if raves still happen!

EL: You have accurately stereotyped me.

aM: Okay. Now, I have to admit my parents were worried about that. And they said, “Ecstasy! Clubs!” and I was like, “No, Mom. That's a different rave. My people are not indoors. We’re outdoors, and we're not paying for stuff, and there's no bar, and there's no drinking. We're just dancing and it's daytime. It was a different thing. But that's really why I got involved in this math thing. In some sense, I wanted to know how all of that music worked, and that music was very mathematical.

EL: Oh.

aM: But then I kind of lost interest in studying the math of that because I just got involved in combinatorics and all the beautiful, theoretical math that fills my spirit and soul. But the origin story is a little bit rave, but mostly that bus.

EL: Yeah. A lot of good things happen on buses.

aM: You guys know about the art gallery theorem? Guarding a museum.

EL: Yeah. Yeah.

aM: What’s the minimum number of guards? Okay, I took the seat of someone—my postdoc was at Bowdoin college, and sadly the person who passed away shortly before I got the job was a combinatorialist named Steve Fisk (I hope I’ve got the name right). In any case, he's in the Proofs from the Book, for coming up with a proof for that art gallery theorem. You know, the famous Proofs from the Book, the idea that all the beautiful proofs are in some book? But yeah, guess where he came up with that, he told the chair of the math department when I started there: on a bus! And he was somewhere in Eastern Europe on a bus, and that's where he came up with it. And it's just like, yeah, things can happen on a bus, you know?

EL: Yeah. Now I want our listeners to, like, write in with the best math they've ever done on a bus or something. A list of bus math.

aM: You also have to include trains, I think, too.

EL: Yeah. Really long buses.

aM: All public transportation.

EL: Yeah. So something that we like to do on this podcast is ask our guests to pair their theorem with something. So what have you chosen to pair with your favorite theorem?

aM: Oh my gosh, I was supposed to think about that. Yes. Okay. Oh, 7.

EL: I feel like you have so many interests in life. You must you must have something you can think of.

aM: Oh, no, it's not a problem. I do currently a lot of mathematics. I'm in my office, sadly, a lot of hours of the day, but sometimes I leave my office and go to the pub down the road. And I call it a pub because it's really empty and brightly lit and not populated by students. It's kind of like a grown up bar. But I do a lot of recreational math there, especially on primitive roots recently. So I think I would pair my 7 theorem with seven sips of Michelob golden draft light. It's just a boring domestic beer. And then I would go across the street to the pizza place that's across from my tavern, and I would eat seven bites of a pizza with pepperoni, sausage, green pepper, and onion.

EL: Nice.

aM: I have a small appetite. So seven people would say yes, he can probably do seven bites before he’s full and needs to take a break.

EL: Or you could you could share it with seven friends.

aM: Yes. Oh, I'm often taking students down there and buying pizza for small sections of research students or groups of seven. Yes.

EL: Nice. So I know you wanted to share some other things with us on this podcast. So do you want to talk about those? Or that? I don't know exactly what form you would like to do this in.

aM: Oh, I wrote a poem. Yeah, I just want to share a poem that I wrote that maybe your listeners might find cute.

EL: Yeah. And I'd like to say I think the first time—I don't think we actually met in person that time, but the first time I saw you—was at the poetry reading at a Joint Math Meeting many years ago.

aM: Oh my gosh! I did this poem, probably.

EL: You might have. I’ll see I remember you. Many people might have seen you because you do stand out in a crowd. You know, you dress in a lot of bright colors and you have very distinctive glasses and hair and everything. So you were very memorable at the time. Yes, right now it's pink, red, and yeah, maybe just different shades of pink.

aM: Yes.

EL: But yeah, I remember seeing you do a poem at this this joint math poetry thing and then kept seeing you at various things and then we met, you know, a few years ago when I was at Eau Claire, I guess, we actually met in person then. But yeah, go ahead, please share your poem with us.

aM: Okay, this is part of the origin story again. This was just shortly after this seven thing from the bus. I was introduced to a proofs class, and they were teaching bijective functions. And I really didn't get the book. It was written by one of my teachers, and I was like, you know, I wrote a poem about it. And I think I understand my poem a little bit more than what you wrote in your book. And like, they actually sing this song now. So they recite it, so say the teachers at Sonoma State, each year to students who are taking this same course. But here it is, I think it's sometimes called a rap because I kind of dance around the room when I sing it. So it's called the Bijection Function Poem. And here you go. Are you ready?

EL: Yes.

KK: Let’s hear it.

aM: All right.

And it clearly follows that the function is bijective
Let’s take a closer look and make this more objective
It bears a certain quality – that which we call injective
A lovin’ love affair, Indeed, a one-to-one perspective.
Injection is the stuff that bonds one range to one domain
For Mr. X in the domain, only Miss Y can take his name
But if some other domain fool should try to get Miss Y’s affection,
The Horizontal Line Police are here to check for 1 to 1 Injection.

(Okay, that’s a little racy.)

Observe though, that injection does not alone grant one bijection
A function of this kind must bear Injection AND Surjection
Surjection!? What is that? Another math word gone surreal
It’s just a simple concept we call “Onto”. Here‟s the deal:
If for EVERY lady ‘y’ who walks the codomain of f
There exists at least one ‘x’ in the Domain who fancies her as his sweet best.
So hear the song that Onto sings – a simple mathful melody:
“There ain’t a Y in Codomain not imaged by some X, you see!”
So there you have it 2 conditions that define a quality.
If it’s injective and surjective, then it’s bijective, by golly!

(So this is the last verse. And there's some homework problems in my last verse, actually.)

Now if you’re paying close attention to my math-poetic verse
I reckon that you’ve noticed implications of Inverse
Inverse functions blow the same tune – They biject oh so happily
By sheer existence, inverse functions mimic Onto qualities (homework problem 1)
And per uniqueness of solution, another inverse golden rule (homework problem 2)
By gosh, that’s one-to-one & Onto straight up out the Biject School!
Word!

aM: Yeah, I never tire that one. I love teaching a proofs class.

EL: Yeah. And you said you use it in your class every time you teach it?

aM: Every time I have to say bijection. I mean, the song works, though. My only drawback in recent times is my wording long ago for “Mr. X in the domain” and “Miss Y can take his name” and the whole binary that this thing is doing. So I do have versions, I have a homosexual version, I have a this version—this is the hetero version—then I have the yet-to-be-written binary-free version, which I don't know how to make that because I was thinking for “Person X in the domain, only Person Y can take his name,” but you know person doesn't work. It's too long syllabically so I'm working on that one.

EL: Yeah.

aM: I’m working on that one.

EL: Well, yeah, modernize it for for the times we live in now.

aM: Yes. I kind of dread reading and reciting this is purely hetero version, you know? And also there's not necessarily only one Miss Y that can take Mr. X’s name. I mean, you know, there's whole different relation groups these days.

EL: Yeah.

aM: But I'm talking about the injection and surjection.

EL: Yeah, the polyamorous functions are a whole different thing.

KK: Those are just relations, they’re not functions. It’s a whole thing.

aM: Oh, yes, relations aren't necessarily functions, but certain ones that be called that right?

EL: Yeah. Well, thank you so much for joining us. Is there anything else you would like to share? I mean, we often give our guests ways to find—give our listeners ways to find our guests online. So if there's anything, you know, a website, or anything you’d like to share.

aM: Can you just link my web page or should I tell you it? [Webpage link here] Actually googling “aBa UWEC math.” That's all it takes. UWEC aBa math. Whenever students can’t find our course notes, I just say like, “I don't know, Google it. There's no way you cannot find our course notes if you remember the name of your school, what you're studying and my name.” Yeah.

EL: We’ll put a link to that also in the show notes for people.

aM: Yeah, one B, aBa, for the listeners.

EL: Yes, that's right. We didn't actually—I said it was the only one spelled that way but we didn't spell it. It's aBa, and you capitalize the middle, the middle and not the first letter, right?

aM: No, yes, that's fine. It looks more symmetric that way.

EL: Yeah. You could even reverse one of them.

aM: I usually write the B backwards. Like the band, but I can't do that usually, though. I don't want to be overkill to the people that I work around. But yes, at the bottom of my webpage, I have the links to videos of me singing various songs to students, complex analysis raps, PhD level down to undergraduate level, just different raps that I wrote for funs.

And I wanted to plug one thing at JMM. I mean, not that it's hard to find it in the program, but I'm an MAA invited speaker this time, and I'm actually scared pooless a little bit to be speaking in one of those large rooms. I don't know how I got invited. But I said yes.

KK: Of course you said yes!

aM: Well, I'm excited to share two research projects that I've been doing with students. Because I like doing research just for the sheer joy of it. And I think the topic of my talk is “A research project birthed out of curiosity and joy” or something like that, because one of the projects I'm sharing wasn't even a paid research project. I just had a student that got really excited to study something I noticed in Pascal's triangle, and these tridiagonal real symmetric matrices. I mean, it was finals week, and I was like, “You want to have fun?” And we spent the next year and a half having fun, and now she's pursuing graduate school, and it's great. It's great, research for fun. But one thing I'm talking about that I'm really excited about is the Fibonacci sequence. And I know that's kind of overplayed at times, but I find it beautiful. And we're looking at the sequence modulo 10. So we're just looking at the last, the units digits.

EL: Yeah, last digits.

aM: And whenever you take the sequence mod anything, it's going to repeat. And that's an easy proof to do. And actually Lagrange knew that long, long ago. But recently, in 1960, a paper came out studying these Fibonacci sequences modulo some natural number, and proved the periodicity bit and proved—there’s tons of papers in the Fibonacci Quarterly related to this thing. But what I'm looking at in particular is a connection to astrology—which actually might clear the room, but I'm hoping not—but the sequence has a length of periods 60. So if you lay that in a circle, it repeats and every 15th value in the Fibonacci number ends in 0. That's something you can see with the sequence, but it’s a lot easier to see when you're just looking at it mod 10. and that's something probably people didn't know now. Every 15th Fibonacci number ends in 0.

KK: No, I didn't know that.

aM: And if it ends in 0, it's a 15th Fibonacci number. And so, it’s an if and only if. And every 5th Fibonacci number is a multiple of five. So in astrology, we have the cardinal signs: Aries, Cancer, Libra and Capricorn. And you and you lay those on the zeros. Those are the zeros. And then the fixed and mutable signs, like Taurus, Gemini, etc, etc. As you move after the birth of the astrological seasons, those ones lay on the fives, and then you can look at aspects between them. Actually, I'm not going to say much astrology, by the way, in this talk. So people who are listening, please still come. It's only math! But I'm going to be looking at sub-sequences, but it got inspired by some videos online that I saw by a certain astrologer. And I—there was no mathematics in the videos and I was like, “Whoa, I can fill these gaps.” And it's just beautiful. Certain sub-sequences in the Fibonacci sequence mod 10 give the Lucas sequences mod 10. The Lucas sequence, and I don't know if your listeners or you guys know what the Lucas sequence is, but it's the Fibonacci sequence, but the starting values are 2 and then 1.

KK: Right.

aM: Instead of zero and one.

EL: Yeah.

aM: And Edward Lucas is the person, actually, who named the Fibonacci sequence the Fibonacci sequence! So this is a big player. And I am really excited to introduce people to these beautiful sub-sequences that exist in this Fibonacci sequence mod 10. It's like, just so sublime, so wonderful.

EL: I guess I never thought about last digits of Fibonacci numbers before, but yeah, I hope to see that, and we'll put some information about that in the show notes too. Yeah, have a good rest of your day.

aM: All right, you too, both of you. Thank you so much for this invitation. I’m happy to be invited.

EL: Yeah, we really enjoyed it. v KK: Thanks, aBa.

aM: All right. Bye-bye.

On this episode of My Favorite Theorem, we talked with aBa Mbirika, a mathematician at the University of Wisconsin Eau Claire. He told us about several favorite theorems of the moment before zeroing in on one of his first mathematical discoveries: a way to determine whether a number is divisible by 7.

Here are some links you may find interesting after listening to the episode.

aBa’s website at UWEC
Snake lemma
Short five lemma
Euler-Fermat’s theorem
Gauss’s primitive roots
Adriana Salerno’s episode of the podcast
Steve Fisk’s “book proof” of the art gallery theorem
Information on aBa’s MAA invited address at the upcoming Joint Mathematics Meetings

Episode 49 - Edmund Harriss

Kevin Knudson: Welcome to My Favorite Theorem, math podcast and so much more. I'm Kevin Knudson, professor of mathematics at the University of Florida, and I am joined today by your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a freelance math and science writer, usually based in Salt Lake City, but today coming from the Institute for Computational and Experimental Research in Mathematics at Brown University in Providence, Rhode Island, where I am in the studio with our guest, Edmund Harriss.

KK: Yeah. this is great. I’m excited for this, this new format where we're, there's only two feeds to keep up with instead of three.

EL: Yeah, he even had a headphone splitter available at a moment's notice.

KK: Oh, wow.

EL: So yeah, this is—we’re really professional today.

KK: That’s right.

EL: So yeah, Edmund, will you tell us a little bit about yourself?

Edmund Harriss: I was going to say I'm the consummate unprofessional. But I'm a mathematician at the University of Arkansas. And as Evelyn was saying, I'm currently at ICERM for the semester working on illustrating mathematics, which is an amazing program that's sort of—both a delightful group of people and a lot of very interesting work trying to get these ideas from mathematics out of our heads, and into things that people can put their hands on, people can see, whether they be research mathematicians or other audiences.

EL: Yeah. I figured before we actually got to your theorem, maybe you could say a little bit about what the exact—or some of the mathematical illustration that you yourself do.

EH: So, yeah, well, one of the big pieces of illustration I've done will come up with a theorem,

EL: Great.

EH: But I consider myself a mathematician and artist. And a part of the artistic aspect, the medium—well, both the medium but more than that, the content, is mathematics. And so thinking about mathematical ideas as something that can be communicated within artwork. And one of the main tools I've used for that is CNC machines. So these are basically robots that control a router, and they can move around, and you can tell it the path to move on and carve anything you like. So even controlling the machine is an incredibly geometric operation with lots of exciting mathematics to it. When I first came across—so one of the sorts of machine you can have is called a five-axis machine. That's where you control both the position, but also the direction that you're cutting in. So you could change the angle as its as its cutting. And so that really brings in a huge amount of mathematics. And so when I first saw one of these machines, I did the typical mathematician thing, and sort of said, “Well, I understand some aspects of how this works really well. How hard can the stuff I don't understand be?” It took me several years to work out just how hard some of the other problems were. So I've written software that can control these machines and turn—in fact, even turn a hand-drawn path into a something the machine can cut. And so to bring it back to the question, which was about illustrating mathematics: One of the nice things about that idea is it takes a sort of hand-drawn path—which is something that's familiar to everyone, especially people in architecture or art, who are often wanting to use these machines, but not sure how—and the mathematics comes from the notion that we take that hand-drawn path, and we make a representation of that on the computer. And so you've got a really interesting function, they're going from the hand drawn path through to the the computer representation, you can then potentially manipulate it on the computer before then passing it again back to the machine. And so now the output of the machine is something in the real world. The initial hand-drawn path was in the real world, and we sort of saw this process of mathematics in the middle.

Amongst other things, I think this is a really sort of interesting view on a mathematical model. you have something in the real world, you pull it into an abstract realm, and then you take that back into the world and see what it can tell you. In this case, it's particularly nice because you get a sense of really what's happening. You can control things, both in the abstract and in the world. And I think, you know, to me that really speaks to the power of thinking and abstraction of mathematics. Of course, also controlling these machines allows you to make mathematical models and objects. And so a lot of my my work is sort of creating mathematical models through that, but I think the process is a more interesting, in many ways, mathematical idea, illustration of mathematics, that the objects that come out

KK: Okay, pop quiz. What's the configuration space of this machine? Do you know what it is?

EH: Well, it depends on which machine.

KK: The one you were describing, where you can where you can have the angles changing. That must affect the topology of the configuration space.

EH: So it’s R3 crossed with a torus.

KK: Okay.

EH: And so even though you're changing the angle of the bit, you really need to think about a torus. It's really also a subset of a torus because you can't reach all angles.

KK: Sure, right.

EH: But it is a torus and not a sphere.

KK: Yeah. Okay.

EH: So if you think about how to get from one position of the machine to another, you really want to—if you think about moving on a sphere, it's going to give you a very odd movement for the machine, whereas moving along a torus gives the natural movement.

KK: Sure, right. All right. So, what's your favorite theorem?

EH: So my favorite theorem is the Gauss-Bonnet.

KK: All the way with Gauss-Bonnet!

EL: Yes. Great theorem. Yeah.

EH: And I think in many ways, because it speaks to what I was saying earlier about the question: as we move to abstraction, that starts to tell us things about the real world. And so the Gauss-Bonnet theorem comes at this sort of period where mathematics is becoming a lot more abstract. And it's thinking about how space works, how we can work with things. You're not just thinking about mathematics as abstracted from the world, but as sort of abstraction in its own right. On the artist side, a bit later you have discussion of concrete art, which is the idea that abstract art starts with reality and then strips things away until you get some sort of form, whereas concrete art starts from nothing and tries to build form up. And I think there's a huge, nice intersection with mathematics. And in the 19th century, you've got that distinction where people were starting to think about objects in their own right. And as that happens, suddenly this great insight, which is something that can really be used practically—you can think about the gospel a theorem, and it's something that tells you about the world. So I guess I should now say what it is.

EL: Yeah, that would be great. Actually, I guess it must have been almost two years ago at this point, we had another guest who did choose the Gauss-Bonnet theorem, but in case someone has not religiously listened to every single episode—

KK: Right, this was some time ago.

EL: Yeah, we should definitely say it again.

EH: So the gospel out there links the sort of behavior of a surface to what happens when you walk around paths on that surface. So the simplest example is this: I start off, I’m on a sphere, and I start at the North Pole and I walk to the equator. At the equator, I turn 90 degrees, I walk a quarter of the way around the Earth, I turn 90 degrees again, and I walk back to the North Pole. And if I turn a final 90 degrees, I’m now back where I started facing in the same direction that I started. But if I look at how much I turned, I didn't go through 360 degrees. So normally if we go around a loop on a nice flat sheet, if you come back to a started pointing in the same direction, you've turned through 360 degrees. So in this path that I took on sphere, I turned through 270 degrees, I turned through too little. And that tells me something about the surface that I'm walking on. So even if I knew nothing about the surface other than this particular loop, I would then know that the surface inside must be mostly positively curved, like a sphere.

And similarly if I did the same trick, but instead of doing it on the sphere, I took a piece of lettuce and started walking around the edge of a piece of lettuce, in fact, I’d find that when I got back to where I started, I’d turned a couple of hundred times round, instead of just once, or less than once, as in the case the sphere. And so in that case, you've got too much turning. And that tells you that the surface inside is made up of a lot of saddles. It's a very negatively curved surface. And one of the motivations of creating this theorem for Gauss, I believe—I always find it dangerous to talk about history of mathematics in public because you never know what the apocryphal stories are—one of the questions Gauss was interested in was not whether or not the earth was a sphere. Well, actually, whether or not the earth was a sphere. So not whether or not it was round, or topologically a ball, but whether it was geometrically really a perfect sphere. And now we can go up into space and have a look back at the earth, and so we can sort of do a three-dimensional version of that, regard the earth as a three dimensional sphere, but Gauss was stuck on the surface of the earth. So he really had this sort of two dimensional picture. And what you can do is create different triangles and ask, for those triangles, what’s the average amount of curvature? So I look at that turning, I look at the total area, the size of the triangle, and ask does that average amount of curvature change as I draw triangles in different places around the earth? And at least to Gauss’s measurements—again, in the potentially apocryphal story I heard—the earth appeared to be a perfect sphere up to the level of measurement, they were able to do then. I think now, we know that the earth is an oblate spheroid, in other words, going between the poles is a slightly shorter distance than across the equator.

KK: Right.

EH: I believe that it was only a couple of years ago that we managed to make spheres that were more perfect than the Earth. So it was sort of, yeah, the Earth is one of the most perfect spheres that anyone has experience of, but it's not quite a perfect sphere when your measurements are fine enough.

KK: So what's the actual statement of Gauss-Bonnet?

EH: So, the statement is that the holonomy, which is a fancy word for the amount of turning you do as you go around a path on the surface, is equal to—now I’m forgetting the precise details—so that turning is closely related to the integral of the Gaussian curvature as you go over the whole surface.

KK: Right.

EH: So it's relating going around that boundary—which is a single integral because you're just moving around a path—to the double integral, which is the going over every point in the surface. And the Gaussian curvature is the notion of whether you're like a sphere, whether you're flat, or whether you're like a saddle at each individual point.

KK: And the Euler characteristic pops up in here somewhere if I remember right.

EH: Yeah. So the version I was giving was assuming that you’re bounding a disk in the surface, and you can do a more powerful version that allows you to do a loop around something that contains a donut.

EL: Yeah, and it relates the topology of a surface, which seems like this very abstract thing, to geometry, which always seems more tangible.

EH: Yeah. Yeah, the notion that the total amount of curvature doesn't change as you shift things topologically.

EL: Right.

EH: Even though you can push it about locally.

KK: Yeah. So if you're if you're pushing it in somewhere, it has to be pooching out somewhere else. Right? That's essentially what's going on, I guess. Right?

EH: Yeah. You know, another thing that's really nice about the the Gauss-Bonnet theorem, it links back to the Euler characteristic and that early topological work, and sort of pulls the topology in this lovely way back into geometric questions, as Evelyn said. And then the Euler characteristic has echoes back to Descartes. So you're seeing this sort of long development of the mathematics that's coming out. It’s not something that came from nowhere. It was slowly developed by insight after insight, of lots of different thinking on the nature of surfaces and polyhedra and objects like that.

EL: Yeah. And so where did you first encounter this theorem?

EH: So this is rather a confession, because—when I was a undergraduate, I absolutely hated my differential equations course. And I swore that I would never do any mathematics involved in differential equations. And I had a very wise PhD advisor who said, “Okay, I'm not going to argue with you on this, but I predict that at some point, you will give me a phone call and say you were wrong. And I don't know when that will be. But that's my prediction.”

KK: Okay.

EH: It did take several years. And so yes, many years later, I'd learned a lot of geometry, and I wanted to get better control over the geometry. So I sort of got into doing differential geometry not through the normal route—which is you sort of push on through calculus—but through first understanding the geometry and then wanting to really control—specifically thinking about surfaces that were neither the geometry of the sphere, the plane, or the hyperbolic plane. Those are three geometries that you can look at without these tools. But when you want to have surfaces that have saddles somewhere and positive curvature—I mean, this relates back to the CNC because you're needing to understand paths on surfaces there in order to take our tool and produce surfaces.

And so I realized that the answers to all my questions lay within differential equations, and actually differential equations were geometric, so I was foolish to dislike them. And I did call up my advisor and say, “Your prediction has come true. I'm calling you to say I was wrong.”

EL: Yeah.

EH: So basically, I came to it from looking at geometry and trying to understand paths on surfaces and realizing from from there that there was this lovely toolkit that I had neglected. And one of the real gems of this toolkit was this theorem. And I think it's a real shame that it's not something that's talked about more. I’ve said this is a bit like the Sistine Chapel of mathematics. You know, most people have heard of the Sistine chapel.

KK: Sure.

EH: Quite a lot of people can tell you something that's actually in it.

EL: Right.

EH: And slowly, only a few people have really seen it. And certainly a very few people have studied it and really looked and can tell you all the details. But in mathematics, we tend to keep everything hidden until people are ready to hear the details. And so I think this is a theorem that you can really play with and see in the world. I mean, it's not a—there are some models and things you can build that are not great for podcasts, but it's something you can really see in the world. You can put it put items related to this theorem into the hands of people who are, you know, eight or nine years old, and they can understand it and do something with it and and see how what happens because all you have to do is give people strips of paper and ask them to start connecting them together, just controlling how the angles work at the corners.

And depending on whether those angles add up to less than 360 degrees—well not the angles at the corner—depending on whether the turning gives you less than 360, exactly 360, or more than 360, you're going to get different shapes. And then you can start putting those shapes together, and you build out different surfaces. And so you can then explore and discover a lot of stuff in a sort of naive way You certainly don't need to understand what an integral is in order to have some experience of what the Gauss-Bonnet theorem is telling you. And so this is sort of it's that aspect, that this is something that was always there in the world. The sort of experiments, the sort of geometry you can look at, through differential geometry and things like the Gauss-Bonnet, that was available to the whole history of mathematics, but we needed to make a break from just geometry as a representation of the world to then sort of step back and look at this result that is a very practical, hands-on one.

You know, if you really want to control things, then you do need to have solid multivariate calculus. So generally, the three-semester course of calculus is often meant to finish with Gauss-Bonnet, and it's the thing that's dropped by most people at the end of the semester, because you don't quite have time for it. And there's not going to be a question on the test. But it's one of those things that you could sort of put out there and have a greater awareness of in mathematics. Just as: this is an interesting, beautiful result. I would say, you know, it's one of humanity's greatest achievements to my mind. You don't have to really be able to understand it perfectly in order to appreciate it. You certainly—as I proved you—can appreciate it without being able to state it exactly.

EL: Yeah, well, you've sold me—although, as we've learned to this podcast, I'm extremely open—susceptible to suggestion.

KK: That’s true. Evelyn's favorite theorem has changed multiple times now. That's right.

EL: Yeah. And I think you brought it back to Gauss-Bonnet. Because when when we had Jeanne Clelland earlier, who said Gauss-Bonnet, I was like, “Well, yeah, I guess the uniformization theorem is trash now”—my previous favorite theorem, but now—it had been pulled over to Cantor again, but you’ve brought it back.

KK: Excellent. All right, so that's another thing we do on this podcast is ask our guest to pair their theorem with something. So Edmund, what pairs well with Gauss-Bonnet?

EH: Well, I have to go with a walnut and pear salad.

KK: Okay.

EL: All right.

KK: I’m intrigued.

EH: Well, I think I've already mentioned lettuce.

EL: Yes.

EH: Lettuce is an incredibly interesting curved surface. Yeah. And then you've got pears, which gives you—

KK: Spheres.

EH: A nice positively curved thing. But they're not just boring spheres.

EL: Yeah.

EH: They have some nice interesting changes of curvature. And then walnuts are also something with very interesting changing curvature. They have very sharply positively curved pieces where they're sort of coming in but then they've got all these sort of wrinkly saddley parts. In fact, one of the applications of the Gauss-Bonnet theorem in nature is how do you create a surface that sort of fits onto itself and fills a lot of space—or doesn't fill that much space but gives you a very high surface area to volume ratio. So walnut is an example—or brains or coral—you see the same forms coming up. And the way many of those things grow is by basically giving more turning as you grow to your boundary.

KK: Right.

EH: And that naturally sort of forces this negatively-curved thing. So I think the salad really shows you different ways in which this surface can—the theorem can affect the behaviors of the surfaces.

EL: Yeah, well, what I want now is something completely flat to put in the salad. Do you have any suggestions?

KK: Usually you put goat cheese in such a thing, but that doesn't really work.

EL: That’s—well, parmesan. You could shave paremesan.

EH: Yeah, shavings of parmesan. Or maybe some thin-cut salami.

EL: Okay.

EH: And so even though those things would bend over—I mean, we’re now on to a different theorem of Gauss, and I don’t meant to corrupt Evelyn away—but you know, when you thinly cut the salami, it can it can bend but it doesn't actually change its curvature.

KK: Right.

EH: Your loops on that salami are going to have the same behavior that they had before. And I guess I should also say that I did create a toy that makes that paper model that I talked about easier to use. You don't have to use tape. You can hook together pieces. And so the toy is called Curvahedra.

KK: I was going to say, you should promote your toy. Yeah.

EH: I’m terrible at self-promotion, yes.

EL: We will help you. Yes, this is a very fun toy. I actually got to play with it for first time a few weeks ago when you did a little short thing and I think when I had seen pictures of it before I thought it was not going to be as sturdy as it is. But this is—yeah, it's called Curvahedra—look it up. It’s these quite sturdy—you know, you don't need to worry about ripping the pieces as you put them together—but you can create these things that look really intricate, and you can create positive curvature, or flat things, or negative curvature in all these different conformations. It's a very fun thing to play with.

EH: And it is a sort of physical version of exactly the Gauss-Bonnet theorem. As you hook together pieces, you're controlling what happens on a loop. And then as you put more of those loops together, you can get a variety of different surfaces, from hyperbolic planes to spheres to—of course, kids have made animals and creatures with it. So you get this sort of control. In fact, it's one of those things that, you put it into the hands of kids, and they do things that you didn't think were really possible with it because their ability to play with these ideas and be free is always so inspiring. So that's what I said, this is a theorem that you can—people can understand as something in the real world. And then you can tell the story of how this understanding of the world is linked directly back to abstract, esoteric mathematics, of the most advanced sort.

KK: Right. One of my favorite things about Curvahedra, though, is the video that you put online somewhere—I think was on Twitter—of it popping out of your suitcase, like you compressed it down into your suitcase to travel home one time?

EH: Yes, I have a model that's about to a two-foot cube. And so you can’t travel with that easily, but it can compress very small. And that same object has been in my suitcase and other things several times, and it's now sitting in my office here.

KK: That’s great fun. And also you've made similar models out of metal, correct?

EH: Yes. So the basic system—not the big one you can crush down to put into suitcases.

KK: No, certainly not.

EH: I’ve made a couple of the spheres. And we're currently working on a proposal to go outside the Honors College at the University of Arkansas. That grew out of a course—it was a design that was created from Curvahedra and other inspirations—by a course I taught with Carl Smith, who is a landscape architect in our landscape architecture school. And so there's going to be—hopefully at some point there's going to be a 12-foot tall Curvahedra-style model outside the Honors College at University of Arkansas.

KK: Very nice.

EL: Nice.

KK: Yeah, this has been great fun. Anything else we want to talk about?

EL: Yeah, well, do you want to say a website or Twitter account or anything where people can find you online?

EH: So I’m actually @Gelada on Twitter, and there is @Curvahedra, and my blog, which is very rarely updated, but has some nice stuff, is called Maxwell Demon.

EL: Yeah, and can you spell your Twitter?

EH: Yes, so Gelada is spelled G-E-L-A-D-A. They are baboons in Ethiopia, or it’s a cold beer in Brazil. I discovered that latter one after being on Twitter, and I regularly get @-ed by people in Brazil, who were not wanting to talk to me at all, but they're asking each other out for beers.

EL: Ah.

EH: And yeah, so then there's also curvahedra.com, where you can get that toy.

EL: Cool. Thanks for joining us.

KK: Yeah, thanks Edmund.

EH: Thank you.

[outro]

On today’s episode, we were pleased to talk with Edmund Harris, a mathematician and mathematical artist at the University of Arkansas, who is our second guest to sing the praises of the Gauss-Bonnet theorem. Below are some links you might find useful as you listen to the episode.



Edmund’s Twitter account, @Gelada

His blog, Maxwell’s Demon


The website and Twitter account for Curvahedra, the toys he makes that help you explore the Gauss-Bonnet theorem and just have a lot of good fun with geometry


Our episode with Jeanne Clelland, who also chose the Gauss-Bonnet theorem


Edmund and Evelyn both attended the Illustrating Mathematics program at the Institute of Computational and Applied Mathematics (ICERM). The program website, which includes videos of some interesting talks at the intersection of math and art, is here.

Episode 48 - Sophie Carr

Kevin Knudson: Welcome to My Favorite Theorem, a math podcast and so much more. I'm one of your hosts, Kevin Knudson. I'm a professor of mathematics at the University of Florida. And here is your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a freelance writer, usually based in Salt Lake City, but currently coming to you from Providence, Rhode Island.

KK: Hooray! Yeah, you're at ICERM.

EL: Yes. The Institute for computational and experimental research in mathematics, an acronym that I am now good at remembering.

KK: I’m glad you told me. I was trying to remember what it stood for this morning because I'm going next week. We'll be in the same place for, like, only the second time ever.

EL: Yeah.

KK: And the universe didn't implode the first time. So I think we're safe.

EL: Yeah.

KK: So the ICERM thing is visualizing mathematics, I mean, we're sort of doing like—next week is about geometry and topology, which since both of us are nominally that, that's just the right place for us to be.

EL: Yeah, it's it's going to be a fun semester. I'm also very excited because I recently turned in—it feels weird to call it a manuscript, but it is being published by a place that publishes books. It is the final draft of a page-a-day calendar about math. And I hope that by the time we air this, I will be able to have a link where people can purchase this and give it to give it to themselves or to their favorite mathematician.

KK: Yeah.

EL: So that's just, every day you can have a little morsel of math to start your morning.

KK: I’m looking forward to that. That’s really exciting. Yeah, that's that's great. All right, so we're continuing a tradition in this episode.

EL: Yes.

KK: So Christian Lawson-Perfect organizes this thing through the Aperiodical called the Great Internet Math-Off [Editor’s note: Whoops, it’s called the Big Internet Math-Off!] of which you were a participant in the first one but not this one, not the second go-around. And we had the first winner on. The winner gets named the World's Most Interesting Mathematician (among those people who Christian could round up and who were free in July). And so we wanted to keep this trend going of getting the most interesting mathematicians in the world on this podcast. And we are pleased to welcome this year's winner, Sophie Carr. Sophie, you want to introduce yourself, please?

SC: Oh, hello, thank you very much. Yeah, I'm Sophie Carr. I studied Bayesian networks at university, and now I own and run a data analytics company.

EL: Yeah, and you’re the most interesting mathematician!

SC: I am! For this year, I am the most interesting mathematician in the world. It's entirely Nira’s fault that I entered because he suggested, and put me forward.

KK: That’s right. Nira Chamberlain was last year's winner. And so when we interviewed him he was sitting in his attic wearing a winter coat. It was wintertime and it seemed very cold where he was. You look very comfortable. It looks like you have a very lovely home in the background.

SC: Yes, I mean, I am in two jumpers. Autumn has definitely arrived. Summer has gone, and it's a little chilly at the moment.

KK: I can only dare to dream. Yeah.

EL: Yeah, Florida and UK have slightly different seasons.

KK: Just a little bit. So you own a consulting company? That’s correct?

SC: Yeah, I do. I set it up 10 years ago now. There’s me and two other people who work with me. We just have an awful lot of fun finding patterns in numbers. I still find it amazing that we're still going. It's just the best fun ever. We get to go and work on all sorts of different problems with all sorts of different people. It's fantastic.

KK: Yeah, that's great. I mean, I'm glad companies are starting to come around to the idea that mathematicians might actually have something to tell them. Right?

SC: Yes. It really is. When you explain to them, you're not going to do magic and it's not a black box, and you can tell them how it works and how it can really make a difference, they are coming around to that.

KK: That’s fantastic. All right, so we're here to talk about theorems.

EL: Yeah. What is your favorite theorem?

SC: My favorite theorem in the whole world is Bayes’ Theorem.

EL: Yay, I'm so glad that someone will be talking about this! Because I know that this is a great theorem and—confession: I just, I don't appreciate it that much.

KK: You know, same.

EL: I need to be told why it's great.

KK: Yeah, I taught probability one time and I said, “Okay, here's Bayes’ theorem.” I kind of went all right. Fine, but of course the question is what's the prior, Mr. Bates? So tell us. Tell us, please.

EL: Yeah, preach!

KK: Preach for Reverend Bayes.

SC: You know, I don't think there's any any preaching needed. Because I always say this. I mean, there are two bits of statistics, there’s the frequentist and the Bayesian. And I always liken it to rugby union, and rugby league, which are two types of rugby in England. It's different codes, but it's the same thing. So to me, Bayes’ theorem, it's just the way that we naturally think. And it's beautifully simple, and all it does is let you take everything that you know and every piece of information that you have, and use that to update the overall outcome. And you're right, that the really big arguments come about from what the prior is. What is the background information that we have, and can we have actually genuinely have a true prior? And some people say no, because you might not have any information. But that's the great bit! Because then you can go and find out what the prior is. You have to be absolutely open about what you're putting in there. I think the really big debate comes around whether people are happy with uncertainty. Are they happy for you to not give an exact answer? If you go and you say, well, this is the prior, this is what we think the information is as well. And we combine these all, combine these priors, and this is the answer. Let's have a debate. Let's start talking about what we can have. Because at its simplest, you've got two things you’re timesing together. Just two numbers. Something that runs your mobile phone. I mean, that’s quite nifty.

KK: So can we can we remind our listeners what Bayes’ theorem actually says?

SC: Okay, so Bayes’ theorem takes two things. It takes the initial, or the prior distribution. Okay, and that's the bit where the argument is. And that might be just, what's the chance of something happening? What do you think the probability is of something happening? And you combine that with something called likelihood ratio. And it's real simple. The likelihood ratio is just a ratio of the probability of the information, or the evidence you have, assuming one hypothesis,divided by the probability of that information assuming another hypothesis. So you just have to have those two values. [And I say you just have to keep it.

And then all you have to do is times them together! That really is it, and when you start to say to people, it's just two numbers—Now, you can turn that into three numbers if you want. You can turn the likelihood ratio bit into its two separate parts. And you can show Bayes’ theorem very, very simply with decision trees, and that was part of the reason I used decision trees in the Math-Off, was just to show the power of something that is really quite simple, that can drive so, so far. And that's what I love about Bayes’ theorem. I always describe it as something that is stunningly elegant, but unbelievably powerful. And I always liken it to Audrey Hepburn. I think if it were to be a person, it would be Audrey Hepburn. Quite small! I'd say it's, it's this amazing little thing that has two simple numbers. But goodness me, getting those numbers, well, I mean, you can just have so much fun! I think you can.

And maybe it's just me that likes finding the patterns in the numbers and finding those distributions. Coming up with the priors. So come on, Kevin, you said, you sat there and your class said, “Well, what's the prior?”

KK: Yeah.

SC: What do you say? How would you tell people to go about finding a prior? Are they going to use their subjective opinion? Are they going to try and find it from data?

KK: Well, that that is the question, isn't it? Right? So, I mean, often, the problem with probability sometimes is that—at least, like, in political forecasting, right—people tend to round up probabilities to 1 or lop them off to zero. Right? So for example, when, you know, when Trump won the election in 2016, everybody thought it was a huge shock. But you know, 538 had it as, you know, Hillary Clinton was a two-to-one favorite. But two-to-one favorites lose all the time, right?

SC: Yeah.

KK: And and so the question then is, yeah, people like to think about one-off events. And then the question is, how do you estimate the probability of a one time event? And you have to make some guess, right, at the prior. And that’s—I think that's where people get suspicious of Bayes’ theorem, or Bayesian statistics, because how you make this estimate? So how do you make estimates in your daily work as a consultant?

SC: Okay, so we do it in a variety of different ways. So if we're really lucky, there’s some historical data we can go looking at.

KK: Sure.

SC: And often just mining that historical data gives you a good starting point. I always get slightly suspicious of flat distributions. Because if we really, really don't know anything other than that, I think maybe a bit of research before where you find the prior is always a good thing. My favorite priors are when we go and talk to people and start to get out of them their subjective opinion. Because I like statistics, I genuinely love statistics, because of the debate that goes on around it. And I think one of the things that people forget about math is that it's such a living subject. And there are so many brilliant debates—and you can call some of them arguments— people are prepared to go and say, “Look, this is my opinion and this is what I think the shape is.” And then we can do the analysis. Inevitably somebody will stand up and go, “Well, that bit is wrong.” Okay, so tell me why!

EL: Yeah.

SC: What evidence have you got for us to change the shape, or why do you think it should be skewed, or Poisson, or whatever we're using? And sometimes, if we haven't got time to do that we can start to put in flat distributions. We can say, “Well, we think it's about normal.” Or “We think on average, it'll be shoved a little bit to the right or a little bit to the left.” That's the three main ways we go about doing it. And I think the ability to be absolutely open and up front about what you know and what you don’t know helps you find that prior. And I don't really understand why people would be scared of running away from that. Why you would not want to say what the uncertainty is or what you're not sure about. But that might go a long way when people think that math is certain.

EL: Yeah.

SC: That when you say the answer is 12, well it’s 12. And not, “Well, it’s 12 because we kind of do it like this, and actually if something changes, that number might change.” And I think getting comfortable with uncertainty and being uncomfortable, is really the crux for developing those priors.

EL: Yeah. Well, I guess for me, it's hard to reason about statistics in a non frequentist way. Meaning—you know, I'm comfortable with non frequentist statistics to a certain degree. But just like what, as you were, saying, like, what does a 30% chance mean if it's not that we could do this 10 times that have it happen three times. But you can't have a presidential election—the same election—10 times, or you can't run Monday’s weather 10 times, or something like that. But it's just hard for me to interpret what does it mean if there isn't a frequentist interpretation?

SC: Yeah. One of the things we found that works really well is if you start showing patterns—and that's why I always talk about patterns, that we find patterns. It's when you're doing Bayesian stats with priors if you start to show the changes as curves, and I don't mean the distribution, but I mean, just as that rising and falling of numbers, people start to understand what's driving the priors, what assumptions are changing those priors. And then you start to see the impact of that, how the final answer changes. That can be incredibly powerful. Often people don't want that set answer. They want to know what the range is, they want to understand how that changes. And showing that impact as a shape—because I think most people are visual. When you show somebody a surface or, you know, a graph, or whatever it is, that's something you can really get a grip with. And actually I come from a Bayesian belief network. So I kind of found out about Bayes’ theorem by chance. I never set off to learn Bayes’ theorem. I set off to design [unintelligible]. That’s what I grew up wanting to do. But I ended up working on Bayesian networks. That’s the short version of what happened.

EL: So, how—was this a “love at first sight” theorem? Or what was your initial encounter with this theorem? And how did you feel about it? Since this is all about subjective feelings anyway!

SC: Well, my PhD was part-time. I spent eight years collecting subjective opinions. So I started a PhD in Bayesian networks, and there was this brilliant representation of a great big probability table. And this is a while ago now. And I’ve moved on a lot into [unintelligible]. But I've got this Bayesian network and supervisor said, “Here we go,” and I went, “Ah, it’s just lots of ovals connected with arrows”

And I went, “There must be something more to this.” And he went, “There’s this thing called Bayes’ theorem that underpins it and look at how it flows. It’s how the information affects it.” And I went, “Okay!” And so, as with all PhDs, you have this pile of reading, which is apparently going to be really, really good for you.

So I got my pile of reading. I went, “Okay.” And genuinely I just thought, “Yeah, it's just kind of how we all work, isn't it?” And I really had not liked statistics at university at all because I’d only really done frequentist statistics. And it’s not like I dislike frequentist statistics. I just didn’t fall in love with it. But when there was something I could see—and I genuinely think it’s because it's visual. I see the shapes move, I could see the numbers flow, I could see the information flow. I thought, “Oh, this is cool stuff. I understand this. I can get my head around this.” And I could start to see how to put things in and how they changed. And I think also I've got at times a very short attention span. So running millions of replicates never really did it for me.

EL: Yeah.

SC: So I had a bit of an issue with frequentist, where we just have to run lots and lots and lots lots of replicates.

EL: Right.

SC: Can we not assume it's kind of like this shape and see what happens? Then change that shape. Look, that’s great. That's much better for me.

EL: Yeah. So it was kind of a conversion experience there.

SC: I think, for people my age, probably. Because I don’t think Bayesian statistics, years ago, was taught that commonly. it's only really in the past sort of maybe decade that I think it's become really mainstream and been taught in the way it is now. Certainly with its its wide applications. That's what I think people just go, something that they've never heard of is now all in the AI world and it’s in your mobile phone, and it's in your medicine, and it's in your spam filters. And when it suddenly becomes really popular, people start to see what it can do. That's when it's taught more. And then you get all these other debates.

KK: So the other fun thing we like to do on this podcast is ask our guests to pair their theorem with something. So what pairs well with Bayes’ theorem?

SC: So this caused a lot of debate in our household.

KK: It always does.

SC: Yeah. And I am going to pair Bayes’ theorem with my favorite food, which is risotto, because risotto only takes three things. It only needs rice and onions and a good stock.

KK: Yes.

SC: And Bayes’ theorem is classically thought with three numbers. And it’s really powerful and gorgeous. And risotto only takes three ingredients, and it’s really gorgeous.

KK: And also, the outcome is uncertain sometimes, right?

SC: Oh, frequently uncertain. And if you change those prior proportions, you will get a very different outcome.

KK: That’s right. You might get soup, or it might might burn.

SC: So, I am going to say that Bayes' theorem is like a risotto.

EL: And you mentioned Audrey Hepburn earlier so maybe it’s even more like sharing a risotto with Audrey Hepburn.

SC: That would be brilliant. How cool would that be?

EL: I know!

SC: I will have my Bayes’ theorem discussion with Audrey Hepburn over risotto. That would be a pretty good day.

EL: Yeah, you could probably get a cardboard cutout. Just, like, invite her to dinner.

SC: Yeah, I'll do that. I'll try and set up a photo, superimpose them.

EL: Yeah.

KK: But Audrey Hepburn should be breakfast somewhere right?

EL: But you can eat risotto for breakfast.

SC: Yeah, you can eat risotto any time of the day.

KK: Sure.

SC: There’s never a bad time for risotto.

KK: No, there isn't. Yeah. My wife actually doesn't like risotto very much, so I never make it.

EL: So is that one of your restaurant foods? So we have this whole like foods that you you tend to order at a restaurant because your partner doesn't like them. And so it's like something that you can—like I don't really like mushrooms, so my partner often will order a mushroom thing at a restaurant.

KK: Yeah, so for me, I don't go out for Italian food because I can make it at home.

EL: Okay.

KK: So I just have a generic I don't I don't eat Italian out. There’s kind of no point, I think.

SC: So you’re right that risotto is my restaurant food because my husband doesn't like it.

KK: Oh.

EL: Aw.

SC: It's my most favorite thing in the world, so yeah, every time we go out, the kids go, “Mom, just don't get the menu. There’s no point. We know what you’re getting.

EL: Yeah. So you said this caused a debate. Did he have a different opinion about what your pairing should be?

SC: Well, there were discussions about whether it was my favorite drink with [a bag of crisps?], and what things could be combined together. And I said, “No, it just has to be risotto.”

KK: Okay. Excellent.

EL: Yeah, we do make that at home. And actually the funny thing is I don't really like mushrooms, but I do like the mushroom risotto that we make.

SC: Oh.

EL: Yeah.

SC: So you've not got a flat prior. You've actually got a little bit of a skew on there.

EL: Yeah, I guess. I’m trying to figure out how to quantify this. Yeah, like my prior distribution for mushroom preference is going to depend on whether it is cooked with arborio rice or not.

SC: See, there we go and you don’t have to worry about numbers you just draw a shape.

EL: Yeah, nice.

KK: Cool. So we also like to give our guests a chance to plug anything they want to plug. Do you have things out there in the world that you want people to know about?

SC: So the only thing I think that's worth mentioning is I do some Royal Institution maths master classes, where we go out and we take our favorite bit of math, and we go and take it to students who are between the ages of about 14 to 17. And that's really what I'm doing coming up in the near future, and they are a brilliant way for lots of people to engage with maths.

EL: Oh, nice.

KK: That’s very cool.

SC: Yeah. They are really good fun.

KK: Have you been doing that for very long?

SC: I’ve been doing them for about two years now. And the first one I ever did was on Bayes’ theorem. And I've never been so terrified, because I don’t teach. And then you have this group of students, and they come up with just the best and most fantastic questions. Every time you do it, you go, “I hadn’t thought of that.”

KK: Yeah.

SC: “And I don't know how to answer that question straight away.” So it's brilliant, and I love doing them. So that's kind of what we've got coming up. And you know, work is just going to be keeping me nicely busy.

EL: Nice.

SC: Yeah.

KK: Well, this has been great fun. Thank you for joining us, and congratulations on being the world's most interesting mathematician for this year.

EL: Yes. Yeah, thanks a lot.

SC: Thank you. I’ve been so excited to do this. I've been listening to your podcast for quite a long time, and I couldn't believe it when you emailed.

okay, thank you very much.

Okay. Thanks.

On this episode, we had the pleasure of talking with Sophie Carr, a statistics consultant and winner of Christian Lawson-Perfect’s Big Internet Math-Off last summer. Here are some links you may enjoy as you listen to this episode.

As we mentioned at the top of the show, Evelyn’s math page-a-day calendar is available for purchase in the AMS bookstore!
Sophie Carr’s twitter account
The Big Internet Math-Off at the Aperiodical
Royal Institution Masterclasses
Sophie Carr is this year’s World’s Most Interesting Mathematician. We also had last year’s World’s Most Interesting Mathematician, Nira Chamberlain, on the show in January. Find his episode here.

Episode 47 - Judy Walker

Kevin Knudson: Welcome to My Favorite Theorem, a podcast about mathematics and all kinds of crazy stuff, and I have no idea what it's going to be today. It is a tale of two very different weather formats today. So I am Kevin Knudson, professor of mathematics at the University of Florida. Here's your other host.

Evelyn Lamb: Hi, I'm Evelyn Lamb. I'm a math and science writer in Salt Lake City, Utah, where I am using the heater on May 28.

KK: Yes, and it's 100 degrees in Gainesville today, and I'm miserable. So this is bad news. Anyway, so today, we are pleased to welcome Judy Walker. Judy, why don't you introduce yourself?

Judy Walker: Hello. Thank you for having me. I'm Judy Walker. I'm a professor of mathematics at the University of Nebraska.

KK: And what else? You're like—

JW: And I am Associate Vice Chancellor for faculty and academic affairs, so that’s, like, Vice Provost for faculty.

KK: That sounds—

EL: Yeah, that does sound very official!

JW: It does sound very official, doesn't it?

KK: That’s right. Like you're weighing T & P decisions in your hands. It's like, you're like Caesar, right? With the thumbs up and the—

JW: I have no official power whatsoever.

KK: Right.

JW: So yes.

KK: But, well, your power is to make sure procedures get followed, right?

JW: Yes. And I have a lot of I have a lot of influence on other things.

KK: Yeah. Right. Yeah. That sounds like a very challenging job.

JW: And for what it's worth, I will add that it is cloudy and windy today. But I think we're supposed to be, like, 67 degrees. So right in the middle.

KK: All right. Great.

EL: Okay, perfect.

KK: So if we could see the map of the US, there'd be these nice isoclines. And here we are. Right. So we're, my mine is very hot. Mine's red. So we're good. Anyway, we came to talk about math. You’re excited to talk about math for once, right?

JW: Exactly. I guess I'm kind of going to be talking about engineering, too. So—

EL: Great.

KK: That’s cool. We like it all here. So what's your favorite theorem?

JW: So my favorite theorem is the Tsfasman-Vladut-Zink theorem.

KK: Okay, that's a lot of words.

JW: It is—well, it’s a lot of names. It's three names. And it's a theorem that is in error-correcting codes, algebraic coding theory. And it's my favorite theorem, because it solves a problem, or maybe not solves a problem, but shows that something's possible that people didn't think necessarily was possible. And the way that it shows that it's possible is by using some pretty high-powered techniques from algebraic geometry, which had not previously been brought into the field at all.

EL: So what is the basic setting? Like what kind of codes can you correct with this theorem?

JW: Right. So the codes are what does the correcting. We don't correct the codes, we use the codes to correct. So I used to tell my — actually, my advisor told me and then I've told all my PhD students — that you have to have a sentence that you start everything with. And so my sentence is: whenever information is transmitted across a channel, errors are bound to occur. So that is the setting for coding theory. You've got information that you're transmitting. Maybe it's pictures from a satellite, or maybe it's just storing things on a computer, or whatever, but you're storing this information. Or you're transmitting this information, and then on the other end, or when you retrieve it, there's going to be some mistakes. And so it's the goal of coding theory to add redundancy in such a way that you can find those mistakes and fix them. Okay?

And we don't actually consider it an error if you fix the mistake. So an error is when so many mistakes happened in the transmission or in the storage and retrieval, that what you think was sent was not what was actually sent, if that makes sense.

KK: Sure. Okay.

JW: So that's the basic setting for coding theory, and coding theory kind of started in 1948 with Shannon's theorem.

KK: Right.

JW: So Shannon's theorem says that reliable communication is possible. So what it says really, is that whatever your channel is, whether it's transmitting satellite pictures, or storing data, or whatever—whatever your channel is, there is a kind of maximum efficiency that's possible on the channel. And so what Shannon’s theorem says is that for any efficiency up to that maximum, and for any epsilon greater than zero, you can find a code that is that efficient has less than epsilon probability of error, meaning the probability that what you sent is not what you think was sent at the end. Okay?

So that's Shannon's theorem. Right? So that's a great theorem.

EL: Yeah.

JW: It’s not my favorite theorem. It’s not my favorite theorem because it actually kind of bothers me.

KK: Why does it bother you?

JW: Yeah, so the reason that bothers me are — there are two reasons it bothers me. One is that it doesn't tell us how to find these codes. It says good codes exist, but it doesn't tell us how to find them, which is kind of useless if you're actually trying to transmit data in a reliable way. But it's actually even worse than that. It's a probabilistic proof. And so it doesn't just say that good codes exists, it says they're everywhere, but you can't find them. Right? So it's like it's taunting us. So I just—. So yeah. So that's Shannon's theorem. And that's why it's not my favorite theorem. But why it's a really great theorem is that it started this whole field. So the whole field of coding theory has been — or of channel coding, at least, which is what we've been talking about is to find those codes, and not just find them, but find them along with efficient decoding algorithms for them. And so that's Shannon's challenge is to find the good codes with efficient decoding algorithms for those good codes. That's 1948, that that started. Right? Okay.

So just as a digression, let me say that most mathematicians and engineers will agree that at this point in time — so a little more than 70 years after Shannon's theorem, that Shannon's challenge has been met, so that we can find these good codes. They're not going to agree on how it's been met. But they'll all agree that it has been met. So on the one hand, in the late ‘90s — mid-to-late 90s — engineers found turbo codes, and they rediscovered low-density parity check codes. And these are codes that in simulations come very, very close to meeting Shannon's challenge. The theory around these codes is still being developed. So the understanding of why they meet Shannon challenge is still try to be solved. But the engineers will say that it's solved, that Shannon's challenge is met because they've got these simulations, and they're so confident about it, that these codes are actually being used in practice now.

EL: So I have a naive question, which is, like, does the existence of us talking over the internet on on this call, sort of demonstrate that this has been met? Like we we are hearing each other — I mean, not with perfect fidelity, but we're able to transmit messages. Is that? Or is that just not even in the same realm?

JW: No, that's exactly exactly what we're talking about, exactly what we're talking about. And not only that, but I don't know if you've noticed, but every once in a while, Kevin gets a little glitchy, and he doesn't move for a while. That's the code catching up and fixing the errors.

KK: Yeah, that's the irony is this this call has been very glitchy for me.

JW: Right.

KK: Which is why we each record our own channel.

EL: Yeah.

JW: Exactly. So in fact, low-density parity-check codes and turbo codes are being used now in mobile phones, in satellite communications, in digital TV, and in Wi-Fi. So that's exactly what we're using.

EL: Okay.

JW: But the mathematicians will say, “Well, it's not really—we’re not really done. Because we don't know why. We don't really understand these things. We don't have all the theoretical underpinnings of what's going on.” A lot of work has been done a lot, and a lot of that is there. But it's still a work in progress. About 10 years ago, kind of on the flip side, polar codes were discovered. And polar codes are the first family of codes to provably achieve capacity. So they actually provably meet Shannon's challenge. But at this moment, they are unusable. There's just still a lot of work to understand how we can actually use polar codes. So the mathematicians say, “We've met the challenge, because we've got polar codes, but we can't use them.” And the engineers say, “We've met the challenge because we've got turbo codes and LDPC codes, but we don't know why.” Right? And that's an oversimplification, but that's kind of the current state. And so different people are working on different things now. And of course, there are other kinds of coding that that aren’t — that isn't really channel coding. There are still all kinds of unsolved problems. So if anybody tells you that coding theory is dead, tell them they're wrong.

EL: Okay!

JW: It’s still very much alive. Okay, so we talked about Shannon's theorem from 1948. And we talked about the current status of coding theory. And my favorite theorem, this Tsfasman-Vladut-Zink, is from 1982. So in the middle.

EL: Halfway in between.

JW: Yes, yes. Just like my weather being halfway in between. Yes. So around this time, in the early ‘80s, and and preceding that, the way that mathematicians were approaching Shannon's challenge was through the study of linear codes. So linear codes are just subspaces, and we might as well think of—in a lot of applications, the data is zeros and ones. But let's go to Fq instead of F2, so q is any prime power.

KK: Okay, so we're doing algebraic geometry now, right?

JW: We’re not yet. Right now, we’re just talking about finite fields.

KK: Okay.

JW: We will soon be be doing algebraic geometry, but not yet. Is that okay?

EL: You’re just trying to transmit some finite set of characters.

JW: Yes, some finite string of characters. Order matters, right? So it's a string. And so the way that we think about it, we can think about it as a systematic code. So the first k characters are information, and then we're adding on n−k redundancy characters that are computed based on the first k.

KK: Okay.

JW: So if we're in a linear setting, then this collection of code words that include the information and the redundancy, that collection of code words is a subspace, say it's a k-dimensional subspace, of Fqn. So that's a linear code. And we can think about that ratio, k/n, as a measure of how efficient the code is.

KK: Right.

JW: Because it's the number of information bits divided by the total number of bits, or symbols, or characters. So, let's call that ratio, R for rate, right? k/n, we’ll call it R. And then how many errors can the code correct? Well, if you look at that Hamming distance—so that's the number of characters and number of positions in which to code words differ—then the bigger that distance, the more errors you can make and still be closest to the code word that was sent. So then that's not really an error. Right? So maybe we say the number of mistakes goes up.

EL: Yeah. So again, let's normalize that minimum distance of the code by dividing by the length of the code. So we have a ratio, let's call that ∂. So that's our relative minimum distance for the code. So one way to phrase this is if we want a certain error-correcting capability, so a certain ∂, how efficient can the code be? How big can R be? Okay, so there are a lot of bounds relating R and ∂, our information rate and our error-correcting capability, or our relative minimum distance. So one that I want I tell you about is that Gilbert-Varshamov bound.

So the Gilbert-Varshamov bound is from 1952. And it says that there's a sequence of codes, or a family of codes if you want, of increasing length, increasing dimension, increasing minimum distance, so that the rate converges to R and the minimum distance to converges to ∂. And R is at least 1−Hq(∂), where Hq is this entropy function. So you may have heard of the binary entropy function, there's a q-ary entropy function, that's what Hq(∂) is. So one such sequence is the so-called classical Goppa codes, and I want to say that that's from, 1956, so just a little bit later. And those codes were the best-known codes from this point of view for about 30 years. Okay, so let me just say that again. So the Gilbert-Varshamov bounds says that there's a sequence of codes with R at least 1−Hq(∂). The Goppa codes satisfy r=1−Hq(∂). And for 30 years, we couldn't find any codes with R greater than.

EL: That were better than that.

JW: Right. That were greater than this 1−Hq(∂).

KK: Okay.

JW: So people at this point were starting to think that maybe the Gilbert-Varshamov bound wasn't a bound as much as it was the true value of how good can R be given ∂, how efficient can codes be given given their relative minimum distance. So this is where this Tsfasman-Vladut-Zink theorem comes in. So in 1978—and Kevin, now we can talk about algebraic geometry. I know you’ve been waiting for that.

KK: All right, awesome.

JW: Yes. Right. So in 1978, Goppa defined algebraic geometry codes. So the way that definition works: remember, a code is just a subspace of Fqn, right? So how are we going to get a set of space of Fqn? Well, what we're going to do is we're going to take a curve defined over Fq that has a lot of rational points, Fq-rational points, right? So we're going to take one of those points and take a multiple of it and call that our divisor on the curve. And then we're going to take the rest of them. And we're going to take the rational functions in this space L(D). D is our divisor, right? So these are the functions that only have poles at this chosen point of multiplicity, at most the degree that we've chosen.

KK: Okay.

JW: And we're going to evaluate all those functions at all the rest of those points. So remember, those functions form a vector space, and evaluation is a linear map. So what we get out is a vector space. So that's our code. And if we make some assumptions, so if we assume that that degree of that divisor, so that multiplicity that we've chosen, is at least twice the genus minus 2, twice the genus of the curve minus 2, then Riemann-Roch kicks in, and we can compute the dimension of L(D). But if we also assume that that degree is less than the number of points that we're evaluating at, then the map is injective. And so we have exactly what the dimension of the code is. The dimension of the code is the degree of the divisor, so that multiplicity that we chose, plus 1 minus the genus. And the minimum distance, it turns out, is at least n minus the degree of the divisor. So lots of symbols, lots of everything.

EL Yeah, trying to hold this all in my mind, without you writing it on the board for me!

JW: I know, I’m sorry. But when you put it all together, and you normalize out by dividing by the length, what you get is that if you have a family of curves with increasing genus, and an increasing number of rational points, then we can end up with a family of codes, so that in the limit, R, our information rate, is at least 1−∂—that’s that relative minimum distance—minus the limit of the genus divided by the number of rational points. Okay. So g [the genus] and n are both growing. And so what's that limit? So that's that was Goppa’s contribution. I mean, not his only contribution. But that's the contribution of Goppa I want to talk about, just that definition of algebraic geometry code. So it's a pretty cool definition. It’s a pretty cool construction. It’s kind of brand new in the sense that nobody was using algebraic geometry in this very engineering-motivated piece of mathematics.

EL: Right.

JW: So here is algebraic geometry, here is a way of defining codes, and the question is, are they any good? And it really depends on what—how fast can the number of points grow, given how fast the genus is growing? So what Drinfeld and Vladut proved—so this is not the TVZ theorem, not my favorite theorem, but one more theorem to get there—Drinfeld and Vladut proved that if you take, if you define Nq(g) to be the maximum number of Fq-rational points on any curve over Fq of genus g, then as you let g go to go to infinity, and for a fixed q, the limit superior, the lim sup, of the ratio g/Nq(g), is at most 1/√(q−1). Okay, fine. Why do we care? Well, the reason we care is that the Tsfasman-Vladut-Zink theorem, which is again my favorite theorem, it says—so actually, my favorite theorem is a corollary of the Tsfasman-Vladut-Zink theorem. So the Tsfasman-Vladut-Zink theorem says that if q is a square prime power, then there's a sequence of curves over Fq of increasing genus that meets the Drinfeld-Vladut bound.

EL: Okay.

JW: Okay, so the Drinfeld-Vladut bound said you can be at most this good. And Tsfasman-Vladut-Zink says, hey, you can do that.

EL: Yeah, it's sharp.

JW: So if we put it all together, then the Gilbert-Varshamov bound gave us this curve, right? So it was a concave-up curve that intersects the vertical axis, which is the R-axis, at 1 and the horizontal axis, which is the ∂-axis, at 1−1/q. So it's this concave-up thing that's just kind of curving out. Then the Tsfasman-Vladut-Zink line—the theorem gives you a line that looks like R=1−∂−1/√(q−1). Right? So it's just a line of slope −1, right, with y-intercept 1−1/√(q−1). So the question is, does that line intersect that curve? And it turns out that if you have q, a square prime power q at least 49, then the line intersects the curve in two points.

EL: Okay.

JW: So what that is really doing for us is it's telling us that in that interval between those two points, we have an improvement on the Gilbert-Varshamov bound. We have better codes than we thought were possible for 30 years.

EL: Wow!

JW: Yes. So that's my, that's my favorite theorem.

KK: I learned a lot.

EL: And where did you first encounter this theorem?

JW: In graduate school? Okay, in graduate school, which was not in 1982. It was substantially after that, but it was said to me by my advisor, “I think there's a connection between algebraic geometry and coding theory, go learn about that.”

KK: Oh.

JW: And I said, “Okay.”

KK: And so two years later.

JW: Right. Right, right. Actually, two years later, I graduated.

KK: Okay. All right. So you’re much faster than I am.

JW: Well, there was four years before that of doing other things.

EL: So was it kind of love at first sight theorem?

JW: Very much so. Because I mean, it's just so beautiful, right? Because here's this problem that nobody knew how to solve, or maybe everybody thought was solved. Because nobody had any techniques that could get any better than the Gilbert-Varshamov bound. And then here's this idea, just way out of left field saying, hey, let's use algebraic geometry to find some codes. And then, hey, let's look at curves with many points. And hey, that ends up giving us better codes than we thought were possible. It's really, really pretty. Right? It's why mathematicians are better than electrical engineers.

EL: Ooh, shots fired!

JW: Gauntlet thrown. I know.

EL: But it does make you wonder how many other things in math will eventually find something like this, like, will will find for these problems—you know, factoring integers or things like this— that we think are difficult, will someone swoop in with some completely new thing and throw it on its head?

JW: Yes. Exactly. I mean, I don't know anything about it. Maybe you do. But the idea that algebraic topology, right, is useful in big data.

KK: Yeah, sure. That's what I've been working on lately. Yeah. Right.

JW: I love that.

KK: Yeah. Sure.

JW: I love that. I don't know anything about it. But I love it.

KK: Well, the mantra is data has shape. Right? So let me just, you know, smack the statisticians here. So they want to put everything on a straight line, right? But a circle isn't a straight line. So what if your data’s a circle? So topology is very good at finding circles.

JW: Nice.

KK: Well, that's the mantra, at least. So yeah. All these unexpected connections really do come up. I mean, it's really—that’s part of why we keep doing what we're doing, right? I mean, we love it. But we never know what's out there. It's, you know, to boldly go where no one has gone before. Right?

JW: Exactly. And Evelyn, it's funny that you should bring up factoring integers, because you know that the form of cryptography that we use today to make it safe to use our credit cards on the internet, that’s very much at risk when quantum computers are developed.

EL: Right.

JW: And so, it turns out that algebraic geometry codes are not being used in practice, because LDPC codes and turbo codes are much more easily implementable. However, one of the very few known so far unbreakable methods for post-quantum cryptography is based on algebraic geometry codes.

KK: Excellent.

EL: Nice.

JW: So even if we can factor integers,

KK: I can still buy dog food at Amazon. Right?

JW: You can still shop at Amazon because of algebraic geometry codes.

EL: Yeah, the important things.

KK: That’s right.

EL: Well, so another thing we like to do on this podcast is invite our guests to pair their theorem with something, the way we would pair food with fine wines. So what have you chosen for this theorem?

JW: So that was very hard. Yeah. I mean, it's just kind of the most bizarre request.

EL: Yeah.

JW: So I mean, I guess the way that I think about this Tsfasman-Vladut-Zink theorem, I was looking for something that was just, you know, unexpected and exciting and beautiful. But I couldn't come up with anything. And so instead, what I'm going with is lemon zest.

KK: Okay.

EL: Okay.

JW: Which I guess can be unexpected and exciting in a dessert, but also because of the way that you just kind of scrape it off that curve of the lemon. And that's what the Tsfasman-Vladut-Zink theorem is doing, is it’s scraping off a little bit of that Gilbert-Varshamov curve.

KK: This is an excellent visual. I've got it. I zest lemons all the time. I understand now. This is it.

EL: Yeah.

JW: There you go.

KK: So all right. Well, we also like to give our guests a chance to plug anything. You wrote a book once. Is that still right? I have it on my shelf.

JW: Yeah. I did write a book once. So that book actually was—Yeah, so I wasn't going to plug anything, but I will plug the book a little bit, but more I'm going to plug a suite of programs. So the book is called, I think, Codes and Curves.

KK: That sounds right.

JW: You would think I would know that.

KK: I’d have to find it. But it is on my shelf.

JW: Yes. It's on mine too, surprisingly, which is right behind me, actually, if you have the video on.

So that book really just a grew out of lecture notes from lectures I gave at the program for women and mathematics at the Institute for Advanced Study. Okay, so I will take my opportunity to plug something to plug that program, to plug EDGE, to plug the Carleton program, and to plug the Smith post-bac program, and to plug the Nebraska conference for undergraduate women in mathematics. So what do all these programs have in common they have in common? They have in common two things that are closely related. One is that they are all programs for women in mathematics. And the other is that they were all the subject of study of a recent NSF grant that I had with Ami Radunskaya and Deanna Haunsperger and Ruth Haas that studied what are the most important or effective aspects of these programs and how can we scale them?

EL: Oh, nice.

JW: Yes. And some of the results of that study, along with a lot of other information, are on our website. That is women do math.org?

EL: I will be visting it as soon as we get off this phone call.

JW: Right. Awesome. I hope it's functioning

KK: And because Judy won't promote herself, I will say, you know, she's been a significant leader in promoting programs for women in mathematics through the University of Nebraska’s math department there. There's a picture of her shaking Bill Clinton's hand somewhere.

JW: Well, that's also on my shelf. Okay. Yeah, I think it's online somewhere, too.

KK: Right. Their program won a national excellence award from the President. Really excellent stuff there at the University of Nebraska. Really a model nationally.

EL: Yeah, I’m familiar with that as one of the best graduate math programs for women.

JW: Thank you.

EL: Yeah. Great job!

EL: Yeah, well, we'll have links to all of those programs on the website. So if you didn't catch one, and you're listening, you can to the website for the podcast and find all those. Yeah. Well, thank you so much for joining us, Judy.

JW: Thank you for the opportunity.

KK: Yeah, this has been great fun. Thanks.

JW: All right. Thank you.

On this episode, we were happy to talk with Judy Walker, who studies coding theory at the University of Nebraska. She told us about her favorite theorem, the Tsfasman-Vladut-Zink theorem. Here are some links to more information about topics we mentioned in the episode.


Goppa (algebraic geometry) code

Hamming distance

Gilbert-Varshamov bound

Judy Walker’s book Codes and Curves

The Program for Women and Mathematics at the Institute for Advanced Study

EDGE 

The Carleton Summer Mathematics Program for women undergraduates

The Smith College post-baccalaureate program for women in math

The Nebraska Conference for Undergraduate Women in Mathematics (Evelyn will be speaking at the conference in 2020)

WomenDoMath.org

Episode 46 - Adriana Salerno

Evelyn Lamb: Hello, and welcome to My Favorite Theorem, a math podcasts where there's no quiz at the end. I’m coming up with a new tagline for it.

Kevin Knudson: Good.

EL: I just thought I'd throw that in. Yeah, so I'm one of your hosts, Evelyn Lamb. I'm a freelance math and science writer from Salt Lake City—or in Salt Lake City, Utah, not originally from here. And here's your other host.

KK: I’m Kevin Knudson, professor of mathematics at the University of Florida in Gainesville, but not from Gainesville. This is part of being a mathematician, right? No one lives where they're from.

EL: Yeah, I guess probably a lot of professions could say this, too.

KK: Yeah, I don’t know. It’s also a sort of a generational thing, right? I think people used to just tend to, you know, live where they grew up, but now not so much. But anyway.

EL: Yeah.

KK: Oh, well, it's okay. I like it here.

EL: Yeah. I mean, it's great here right now it's spring, and I've been doing a ton of gardening, which always seems like such a chore and then I'm out smelling the dirt and looking at earthworms and stuff, and it's very nice.

KK: I’m bird watching like crazy these days. Yesterday, we went out and we saw the bobolinks were migrating through. They're not native here, they just come through for, like, a week, and then they're gone.

EL: The what?

KK: Bobolinks, B-O-B-O-L-I-N-K. They kind of fool you, they look a little bit like an oriole, but the orange is on the wrong side. It's on the back of the neck instead of underneath.

EL: Okay, I'll have to look up a picture of that later.

KK: And then this morning for the first time ever, we had a rose-breasted grosbeak at our feeder. Never seen one before and they're not native around here, they just migrate through. So this is

EL: Very nice. Yes.

KK: This is what I'm doing in my late middle age. This is what I do. I just took up bird watching, you know?

EL: Yeah. Well, I can see the appeal.

KK: Yeah, it's great.

EL: Yes. But we are excited today to be talking with Adriana Salerno. Do you want to introduce yourself?

Adriana Salerno: Hi. Yeah, I'm Adriana Salerno. Now I am an associate professor of math at Bates College in Maine. And I am also not from Maine. I live in Maine. I'm originally from Caracas, Venezuela, so quite a ways away.

EL: Yeah.

AS: Again, you don't choose where you live, but maybe you get to choose where you work. So that's nice.

EL: Yeah. And you're you're not only a professor there, but you're also the department chair right now, right?

AS: Oh, yeah. Yeah, I'm trying to forget. No, I’m kidding.

EL: Sorry!

KK: You know, speaking of, before we we started recording here, I spent my afternoon writing annual faculty evaluations. I’m in the first year as chair. I have 58 of them to write.

AS: Oh, I don't have to do those, which I'm very happy about. But we are hiring a staff position, and I'm in charge of that. And that's been a lot.

EL: And we actually met because both of us have done this mass media fellowship for people interested in math or science and writing. And so you've done a lot of writing not for mathematicians as well, throughout your career path.

AS: Yeah, yeah. I mean, I did the mass media fellowship in 2007. And since then, I've been trying to write more and more about mathematics for a general audience. These days, I mostly spend time writing for blogs for the AMS. And right now I'm editing and writing for inclusion/exclusion. I wish I had more time to write than I do. It's one of those things that I really like to do, and I don't think I do enough of, but these opportunities are great because I get to use those—or scratch that itch, I guess, by talking to you all.

EL: Yes.

KK: Well, so speaking of, we assume you have a favorite theorem that you want to tell us about. What is it?

AS: Well, so it's always hard to decide, right? But I guess I was inspired by a conversation I had with Evelyn at the Joint Math Meetings. So I've decided my favorite theorem is Cantor's diagonalization argument that the real numbers do not have the same cardinality as the natural numbers.

EL: Yes, and I’m so excited about this! Ever since we talked at the Joint Meetings, I’ve been very excited about getting you to talk about this.

AS: Good. Good.

EL: Because really, it’s such a great theorem.

AS: Yeah. Well, I was thinking about it today. And I'm like, how am I going to explain this? But I have chosen that, and I'm sticking with it. Yeah.

EL: Yes.

KK: Good.

AS: So yeah, it’s—one of the coolest things about it is sort of it’s this first experience that you have, as a math student—at least it was for me—where you realize that there are different sizes of infinity. And so another way of saying that is that this theorem shows, without a doubt, I believe—although some students still doubt me after we go over it—it shows that you can have different sizes of infinity. And so the first step, even, is to say, “How do you decide if two things have the same size of infinity?” Right? And so it's a very, very lovely sort of succession of ideas. And so the first thing is, how do you decide that two things are the same size? Well, if they're finite, you count them, and you see that you have the same number of things. But even when things are finite—and say, you're a little kid, and you don't know how to count—another way of saying there's the same number of things is if you can match them up in pairs, right? So you know, if you want to say I have the same number of crayons as I have apples, you can match a crayon to an apple and see that you don't have anything left over, right?

EL: Yeah.

AS: And so it's just a very natural idea. And so when you think about infinite sets—or not even infinite sets—but you can think of this idea of size by saying two things are the same size if I can match every element in one set to every element in another set, just one by one. And so I really like, I'm borrowing from Kelsey Houston-Edwards’ PBS show, but what I really like that she said that you have two sets, and every element has a buddy, right? And so then I love that language, and so I'm borrowing from from her. But then that works for finite sets, but you can extend it to an infinite set.You can say, for example, that two infinite sets are the same size if I can find a matching between every element in the first set and every element in the second set. It’s very hard to picture in your head, I think, but we're going to try to do this. So for example, you can say that the natural numbers, the counting numbers, 1, 2, 3, 4, etc, have the same size as the even numbers, because you can make a matching where you say, “Match the number 1 with the number 2 on the other side. And then the number 2, with the number 4 on the other side.” And you have all the counting numbers, and for every counting number, you have two times that number as the even buddy.

EL: Yeah. And I think this is, it's a simple example that you started with, but it even hints at the weirdness of infinity.

AS: Yeah.

EL: You’ve got this matching, but the even numbers are also a subset of the natural numbers. Ooh, things are going to get a little weird here.

KK: Clearly, there aren’t as many even numbers, right?

AS: Yeah.

KK: This is where you fight with your students all the time.

AS: That’s exactly—so when you're teaching this, the first thing you do is talk about things that have the same cardinality. And then everybody, it can take a while, you know, like, infinity is so weird that you can actually do these matching. So Hilbert’s infinite hotel is a really great way of doing this sort of more conceptually. So you have infinitely many rooms. And so for example, suppose that rooms numbers from 1, 2, 3, to infinity, mean, and so on. Yes, you have to be careful because infinity is not a number. You have to be careful with that. But say that all the rooms are occupied. And so then, you know, say someone shows up in the middle of the night, and they say, “I need a room.” And so what you do if you're the hotel manager is you tell everyone to move one room over. And so everyone moves one room over and you put this person in, and room number one. And so that's another way of seeing that. So the one-to-one pairing, or the matching here is every person has a room. And so the number of rooms and the number of people are the same—the word is cardinality because you don't want to say number because you can't count that.

KK: Right.

AS: And so you you say cardinality instead. But it's really weird, right? Because the first time you think about this, you say, “Well, you know, there's infinity, and there's infinity plus one.” That's like the kind of thing that you would say as a kid, right? And they're the same! When you have the natural numbers and the natural numbers and one extra thing, or like with zero, for example—unless you're in the camp that says zero is an actual number—but we're not going to get to that discussion right now.

KK: I’m camp zero is a natural number.

AS: Okay. I feel like I know maybe half people who say zero is a natural number and the other half say it's not. And I don't think anyone has good arguments other than, ah, it must be true! And so then the cool thing is, once you start doing that, then you start seeing, for example—and these are, these are kind of tricky examples, it can get tricky. Like, you can say that the integers like the positive whole numbers, negative whole numbers and zero, that also has the same cardinality as the natural numbers. Because you can just start with zero—I mean, basically, when you want to say that something has the same cardinality as the natural numbers, what you're really trying to do is to find a buddy, so you're trying to pair someone with one or two, or three. But really, what you can do is just list them in order, right? Like you can have like the first one, the second one, the third one, the fourth one, and you know that that's a good matching. It's like the hotel. You can put everyone in a room. And then you know they're the same number. Everyone has a room. So with the integers, for example, the whole numbers, positive, negative and zero, then you can say, “Okay, put zero first, then one, then negative one, and two, then negative two then three, then negative three,” and then they're the same size, right? And so once you start thinking about this—I remember this pretty clearly from from college—once you start thinking about this, then you're like, “Well, obviously, because infinity is infinity.” That’s the next step. So the first step is like, well no, infinity plus one and infinity are different. But then you get convinced that there is a way of matching things that where you can get things that seem pretty different, or a subset of a set, and they have the same cardinality. And then you go the other direction, which is “Well, of course, anything infinite is going to be the same size as anything else that's infinite.” And so then it turns out that even the rationals are the same size as the natural numbers. And that's way more complicated than we have time for. But if you add real numbers, meaning irrationals as well, then you have a whole different situation.

KK: You do indeed.

AS: It’s mind blowing, right? And so if you just think about the real numbers between zero and one, so just get go real simple. I mean, small, relatively. So you're just looking at decimal expansions. And so if those numbers had the same cardinality as the natural numbers, then you should be able to have a first one and a second one and a third one, and a fourth one. Or you can pair one number was the number 1, one number with the number 2, etc. And that list should be complete, and in the words of Kelsey Houston-Edwards, everyone should have a buddy. And so then, here's the cool thing, this is a proof that these two sizes of infinity are not the same, and it's a proof by contradiction, which is, again, your favorite proof when you are learning how to prove things. I mean, when I was learning proofs, I wanted to do everything by contradiction. So proving something by contradiction means you want to assume, “Well, what if we can list all the all the real numbers?” There’s a first one, a second one, a third one, etc. So Cantor’s amazing insight was that you can always find a number that was not on that list. Every time you make this list: a first one, a second one, a third one… there is some missing element.

And so you line up all your decimals. So you have the first number in decimal. And so you have like, you know, 0.12345… or something like that. And then you have the next one. And the next one. And like, I mean, this is really hard to do verbally, but we're going to do it. And so you sort of line them up, and you have infinite decimals. So you have point, a whole bunch of decimals, point, a whole bunch of decimals. And so you can make a missing number by taking that first number in the first decimal place a just changing that number. Okay, so if it was a 1, you write down a 2. And so you know, because we’ve known how to compare decimals since we were little kids, that what you need to compare is decimal place by decimal place. So these are different because they're different in this one spot, right? And then you go to the second number, and the second decimal point. And then you say, “Well, whatever number I see there, I'm going to make the second decimal point of my new number different.” So if you had a 3, you change it to a 4, whatever it is, as long as it's not the original number. And and this is why it's called the diagonalization argument, or the diagonal argument, because you have lined all those numbers up, and you can go through the diagonal, and for each one of those decimal points, at each decimal place, you just change the value. And what you're going to get is a number, another real number, infinitely many decimals, and it's going to be different from every number on your list, just by virtue of how you made it. And so then, what that shows is that the answer to the “what if” is: you can’t. The “what if” is, if you have a list of all real numbers, it's not complete. So there is never going to be a way that you can make that list complete. And this is the part where every time I tell my students, at some point, they're like, “Wait, there are different sizes of infinity? What?” Then—and that’s sort of lovely, because it's just this this mind-blowing moment where you've convinced yourself, by the way, that you were to infinity is infinity, and then you realize that there's something bigger than the cardinality of the natural numbers. And and then it's really fun when you tell them, “Well, is there something in between?” They’re like, “Of course! There must be!” And then you're like, “Wait, no one knows.”

KK: Maybe not.

EL: Yeah.

AS: So yeah, I just love that argument. And I love how simple it is. And at the same time, it's, simple, but it's very, very deep, right? You really have to understand how these numbers match up with each other. And it requires a big leap of imagination to just think of doing this and realizing that you could make a number that was not on this infinite list by just doing that simple trick.

EL: Yeah.

AS: And so I just think it's a really, really beautiful theorem. And then I also have a really personal connection to this theorem. But it's one of my favorite things to teach. And I'm going to be teaching at this term, and I’m really looking forward to seeing how that how that lands. Sometimes it lands really well. Sometimes people are like, “Eh, you’re just making stuff up.” Yeah.

EL: Yeah.

KK: Well, then you can really blow their minds then when you show them the Cantor set, right?

AS: Yeah, yeah.

KK: And say, “Well, look, I mean, here's this subset of the reels that has the same cardinality, but it's nothing.”

AS: Exactly. Yeah, there's nothing there. Yeah.

EL: Yeah. I remember, then, when I first saw this argument, really carefully talking myself through, “Like, okay, but what if I just added that number I just made to the end of the list? Why wouldn't that work?” And trying to go through, like, “Why can't I—Oh, and then there must be other numbers that don’t fit on the list either.” It's not like we got within 1 of being the right cardinality.

AS: Right.

EL: For these infinite number. So yeah, it's a really cool idea. But you said you had some personal connections to this. So do you want to talk more about those?

AS Sure. So I am from Venezuela, and I went to college there. And I liked college, it was fine. I knew—Well, one thing that you do have to decide when you're a student in high school is, you don't really apply to college, you apply to a major within the college. And so then I knew I wanted to do math. And I signed up for math at a specific university. And so then the first year was very similar to what you would do in the States, which is sort of this general year where everybody's thinking calculus, or everybody's taking—you have some subset of things that everybody takes. And then your second year, you start really going into the math major. And so this was my first real analysis class. This was my first serious proof-y class in my university. And we learned Cantor’s diagonalization argument, which was pretty early. But I loved this argument. I felt so mind-blown. You know, I was like, “This is why I want to do math,” you know, I was just so excited. And I knew I understood everything. And so I took the exam, and I got horrible grade. And in particular, I got zero points on the “prove that the real and the natural numbers don't have the same cardinality.” And so I went to the professor, and I saw my exam, and I was really confused. And I went to the professor, and I said, “I really don't understand what's wrong with this problem. Could you help me understand?” Because I thought I understood this. And then—you know, that's a typical thing. I probably said it in a more obnoxious way than I remember now. But I felt like I was being pretty reasonable. I was not the kind of kid that would go up to my professors too often to ask for points. I really was like, “I don't know what I did wrong.” And especially because I felt like I really got it.

EL: Right.

AS: And so then he just looked at me and said, “If you don't understand what's wrong with this problem, you should not be a math major.” And that was it. That was the end of that conversation. Well, I still don't know what's wrong with this problem, and now you just told me I need to do something else. Just go do something else at a different school. Right? And I mean, I don't know that that was particularly sexist. But I do know that I was the only woman in that class, and I know that I felt it a lot. I think he probably would have said that—I really do think that he in particular would have said that to any student. I don’t think it was just me being female that affected that at all. But I do think that if I had been less stubborn about my math identity, I might have taken him up on that. But I was just like, “No, I'm going to show you!” And eventually I got an A in his class. He taught real analysis every semester, so I had to take the class with him every time and at some point, I cracked his code. And he at some point respected me, and thought I deserved to be there. But he was just very old-fashioned. You know, I don't think it's even sexism. It's just very, very, like, this is how we do things. And then I went—eventually, I did talk to someone. I think it was a teaching assistant. And I was like, “I don't know what's wrong with this problem.” And he looked at it. And he said, “Well, here's the problem. When you were listing—so you needed to list all these generic numbers and their decimal expansion. And I did, “Okay, the first number is point A1, A2, A3, etc. The second number is point B1, B2, B3, etc. The third one is point C1, C2, C3, etc, dot dot dot, right? And he said, “You have listed 26 numbers. And that's not going to be an infinite list.” Right?

KK: That’s cheap.

AS: And I was just like, “Okay, but I got the idea, right?” I was like, “Okay, it's true.” He’s like, “The way you wrote it is incorrect.” And I'm like, sure.

EL: Sort of.

KK: I’ve written that same thing on a chalkboard.

AS: You know, this shows you—like, fine, you can be more careful, you can be more precise, but from this, you shouldn't be a math major? That’s pretty intense.

EL: Yeah.

AS: And I knew the mechanics, I knew what was supposed to be happening, I knew how to make the missing number, right? Like you just need A1: you change it to some other number, B2: you change it to some other number, C3: you change it to some other number. And so, I just thought—I mean, that was a moment where I was just literally told I should not be in math because I made a silly mistake. And it was a moment where I realized that—now looking back, I realize my math identity was pretty strong, because I just said, “Well, ask someone else to see what was wrong, and I'm not going to ask this guy anymore because it's clear what he thinks.”

EL: Yeah.

AS: And sort of the stubbornness of, “Well, I’ll show him that I do deserve to be here.” But I think of all the students who might have taken classes with him, who would have heard that and then been like, “Yeah, maybe I need to do something else.” I mean, it just makes me really sad to hear, especially now that I'm a professor, and teaching these kinds of things. It just makes me sad to see which people were just scared away by someone like that, you know?

EL: Yeah.

AS: So that was a big moment for me. Yeah.

EL: Yeah. Quite a disproportionate response to, what’s basically a bookkeeping difficulty.

AS: Yeah.

EL: So, you know, we like to get our mathematicians to pair their theorems, with something on this show. And what have you chosen as your pairing for Cantor's diagonalization argument?

AS: Well, now that you suggested, music and other things, I'm maybe changing my mind.

EL: You could pair more than one thing.

AS: I was trying to find something that was just like—I need to sort of express the sort of mind-blowing nature of this, right? And so I was like, a tequila shot! You know, really just strong. And like, “Whoa, what just happened?” And so that was one thing that I thought about. And then—I don't know, just mind-blowing experiences, like, when I saw the Himalayas from an airplane, or when—you know, there are some moments where you're just like, “I can't believe this exists.” I can't believe this is a thing that I get to experience. So I guess, you know, there's been—most of these have been with traveling, where you just see something that you're just like, “I can't believe that I get to experience this.” And so I think Cantor's diagonalization argument is something like that, like seeing this amazing landscape where you're just like, “How does this even exist?”

EL: Yeah, I like that. I mean, I've had that experience looking out of airplane windows too. One time we were just flying by the coast of Greenland. And these fjords there. Of course, an airplane window is tiny and it's not exactly high-definition picture quality out of the thick plastic there, but it just took my breath away.

AS: Yeah.

EL: Yeah, I like that. And we can even invite our listeners to think of their own mind-blowing favorite experiences that they've they've had. Hopefully legal experiences in their jurisdiction.

KK: Well, oh wait, it's not 4/20 anymore. Oh, well. So we also like to invite our guests to plug anything they want to plug. So you write for the AMS, the inclusion/exclusion blog, are there other places where we might find your mathematical writing for the general public?

AS: Well, that's my main plug and outlet right now. But I I do write for the MAA Focus magazine sometimes. That's sort of my main, and sometimes the AWM newsletter. So you might find some of my writing there. And the blog. I mean, again, now that I'm chair and doing a lot of other things, I'm not writing as much, but I definitely like to—I’ve gotten really into maybe this is a weird plug, but I've gotten really into storytelling.

EL: Oh yeah, you’ve been on Story Collider?

AS: Yeah, I was on one Story Collider. I've done some of the local stuff. But you can find me on the internet telling stories about being a mathematician. Some of them about some pretty fantastic experiences, and some not so great experiences.

EL: Yeah. Okay. Yeah. Well, we'll link to your Twitter, and that can help people find you too.

AS: Oh, yeah. Cool.

EL: Thanks a lot for joining us.

AS: Yeah. Thanks for having me and listen to me ramble about infinity.

EL: Oh, I just love this theorem so much.

KK: Yeah, we could talk about infinity all day. Thanks, Adriana.

AS: Yeah. Thank you so much.

We were excited to have Bates College mathematician Adriana Salerno on the show. She is also the chair of the department at Bates and a former Mass Media Fellow (just like Evelyn). Here are some links you might enjoy along with this episode.


Salerno's website

Salerno on Twitter
AAAS Mass Media Fellowship for graduate students in math and science who are interested in writing about math and science for non-experts
Hilbert’s Infinite Hotel
Evelyn’s blog post about the Cantor set
Salerno’s StoryCollider episode
The inclusion/exclusion blog, an AMS blog about diversity, inclusion, race, gender, biases, and all that fun stuff

Episode 45 - Your Flash Favorite Theorems

Kevin Knudson: 1-2-3

Kevin Knudson and Evelyn Lamb: Welcome to My Favorite Theorem!

KK: Okay, good.

EL: Yeah.

[Theme music]

KK: So we’re at the JMM.

EL: Yeah, we’re here at the Joint Math Meetings. They’re in Baltimore this year. The last time I was at the Joint Meetings in Baltimore I got really sick, but so far I seem to not be sick.

KK: That’s good. You’ve only been here a couple of days, though.

EL: Yeah. There’s still time.

KK: Yeah, so I’ve only been to the Joint Meetings one other time in my life, 20 years ago as a postdoc in Baltimore. I’ve just got a thing for Baltimore, I guess.

EL: Yeah, I guess so.

KK: So people may have seen this on Twitter. Fun fact: this is our first time meeting in person.

EL: Yeah.

KK: And you’re every bit as charming in real life as you are over video.

EL: And you’re taller than I expected because my first approximation of all humans is that they are my height, and you are not my height.

KK: But you’re not exceptionally short.

EL: No.

KK: You’re actually above average height, right?

EL: I’m about average for a woman, which makes me below average for humans.

KK: Well, if we’re going to the Netherlands, for example, I’m below average for the Netherlands.

EL: Yes.

KK: So I’m actually leaving today. I was only here for a couple of days. I was here for the department chairs workshop. You’re here through when?

EL: I’m leaving on Friday, tomorrow. Yeah, while we’ve been here we’ve been collecting flash favorite theorems where people have been telling us about their favorite theorem in a small amount of time. So yeah, we’re excited to share those with you.

KK: Yeah, this is going to be a good compilation. I’m going to try to get a couple more before I leave town. We’ll see what happens.

EL: Yeah. All right.

KK: Enjoy.

EL: I am here with Eric Sullivan. Can you tell us a little bit about yourself?

Eric Sullivan: Yeah, I'm an associate professor at Carroll College in Helena, Montana, lover of all things mathematics.

EL: And here with me in the Salt Lake City Airport, I assume catching a connecting flight to the Joint Math Meetings.

ES: You got it.

EL: All right, and what is your favorite theorem, or the favorite theorem you'd like to tell me about right now?

ES: Oh, I have many favorite theorems, but the one that's really coming to mind right now, especially since I'm teaching complex analysis this semester, are the Cauchy-Riemann equations.

EL: Very nice.

ES: Giving us a beautiful connection between analytic functions, and ultimately, harmonic functions. Really lovely. And it seems like a mystery to my students when they first see it, but it's beautiful math.

EL: Yeah, it is. They are kind of mysterious, even after you've seen them for a while. It's like, why does this balance so beautifully?

ES: Right? And the way you get there with the limit, so I'm just going to take the limit going one way, then I’ll take the limit going the other way and voila, out comes these beautiful partial differential equations.

EL: Yeah, very lovely. And I know I'm putting you on the spot. But do you have a pairing for this theorem?

ES: Ooh, a pairing? Oh boy, something was a very complex taste. Maybe chili.

EL: Okay.

ES: I’ll say chili because there's all sorts of flavors mixed in with chili, and complex analysis seems to mix all sorts of flavors together.

EL: All right, I like it. Well, thank you. This is the first lightning My Favorite Theorem I'm recording so far at the joing meetings, or even before, on the way, so yeah, thanks for joining me.

Courtney Gibbons: I'm Courtney Gibbons. I'm a professor at Hamilton College in upstate New York. And my favorite theorem is Hilbert’s Nullstellensatz, which translates to zero point theorem, but if you run it through Google Translate, it's actually quite beautiful. It's like the “empty star theorem” or something like that. It's very astronomical. And I love this theorem because it's one of those magical theorems that connect one area that I love, algebra, to another area that I don't really understand, but would like to love, geometry. And I find that in my classes, when I ask someone, “What's a parabola?” I have a handful of students who do some sort of interpretive dance. And I have a handful of students were like, “Oh, it's like y equals some x squared stuff.” And I'm like, “I'm with you.” I think of the equation. And some people think of the curve, the plot, and that's the geometric object, and the Nullstellensatz tells you how to take ideals and relate them to varieties. So it connects algebra and geometry. And it's just gorgeous, and the proof is gorgeous, and everything about it is wonderful, and David Hilbert was wonderful. And if I were going to pair it with something, I’d probably pair it with a trip to an observatory, so that you could go appreciate the beauty of the stars, and think about the wonderful connectedness of all of mathematics and the universe. And maybe you should have, like, a beer or something too.

EL: Why not?

CG: Yeah. Why not? Exactly.

EL: Good. Well, thank you. Absolutely.

KK: All right, JMM flash theorem time. Introduce yourself, please.

Shelley Kandola: Hi. My name is Shelly Kandola. I'm a grad student at the University of Minnesota.

KK: And it’s warmer here than where you are usually.

SK: Yeah, it's 15 degrees in Minnesota right now.

KK: That’s awful.

SK: Yeah.

KK: Well anyway, we’ve got to be quick here. What's your favorite theorem?

SK: The Banach-Tarski paradox.

KK: This is an amazing result that I still don't really understand and I can't wrap my head around.

SK: Yeah, you've got a solid sphere, a filled-in S2, and you can cut it into four pieces using rigid motions, and then put them back together and get two solid spheres that are the same size as the original.

KK: Well, theoretically, you can do this, right? This isn't something you can actually do, is it?

SK: Physically no, but with the power of group theory, yes.

KK: With the power of group theory.

SK: The free group on two generators.

KK: Why do you like this theorem so much?

SK: So I like it because it was the basis of my senior research project in college.

KK: It just seems so weird it was something you should think about?

SK: Yeah, it intrigued me. It's a paradox. And it's the first theorem I dove really deep into, and we found a way to generalize it to arbitrarily many dimensions with one tweak added.

KK: Cool. So what does one pair with the Banach-Tarski paradox?

SK: One of my favorite Futurama episodes. There's this one episode where there's a Banach-Tarski duplicator, and Bender jumps into the duplicator, and he makes two more, and he wants to build an army of himself.

KK: Sure.

SK: But every time he jumps in, the two copies that come out, are half the size of the original. He ends up with an army of nanobots. It contradicts the whole statement of the paradox that you're getting two things back that are the same size as the original.

KK: Although an army of Benders might be fun.

SK: Yeah, they certainly wreak havoc.

KK: Don’t we all have a little inner Bender?

SK: Oh yeah. He's powered by beer.

KK: Well, thanks for joining us. You gave a really good talk this morning.

SK: Thanks.

KK: Good luck.

SK: Thank you for having me.

KK: Sure.

David Plaxco: My name is David Plaxco. I'm a math education researcher at Clayton State University. And my favorite theorem is really more of an exercise, I think most people would think. It's proving that the set of all elements in a group that conjugate with a fixed element is a subgroup of the group. I'll tell you why. Because in my dissertation, that exercise was the linchpin in understanding how students can learn by proving.

EL: Okay.

DP: So I was working with a student. He had read ahead in the textbook and knew that not all groups are commutative, so you can't always commute any two elements you feel like. And he generalized this to thinking about inverses. He didn’t think that every inverse was necessarily two-sided, which in a group you are. Anyway, so he was trying to prove that that set was a subgroup and came to this impasse because he wanted to left cancel and right cancel with inverses and could only do them on one side. And then he started to question, like, maybe I'm just crazy, like maybe you can use the same inverse on both sides. And then he proved it himself using associativity. So he made, like, I call it John’s lemma, he came up with this kind of side proof to show that, well, if you're associative and you have a right inverse and a left inverse, then those have to be the same. And then he came back and was able to left and right cancel at free will any inverse, and then proved that it was a subgroup, so through his own proof activity, he was able to change his own conceptual understanding about what it means to be an inverse, like how groups work, all these things, and it gave him so much more power moving forward. So that's how that theorem became my favorite theorem because it gave me insight into how individuals can learn.

EL: Nice. And do you have a pairing for this theorem?

DP: My diploma. Because it helped me get it.

EL: That seems appropriate. Thanks.

DP: Thanks.

Terence Tsui: So I'm Terrance, and I'm currently a final year undergraduate studying in Oxford. My favorite theorem is actually a really elegant proof of Euler’s identity on the Riemann zeta function. We all know that the Riemann zeta function is defined in a way of the sum of 1/ks where k runs across all the natural numbers. But at the same time, Euler has given a really good other formulation: we say status is the same as the infinite product of 1-1/ps, where p runs across the primes. And then it's really interesting, because if you look at you see, on one hand, an infinite some, and on the other hand, you have an infinite product. And it’s very rare that we see that infinite sums and infinite products actually coincide. And they’re only there because it is a function that actually works on nearly every s larger than 1. And that means that this beautiful, elegant identity actually runs correct for infinitely many values. And the most interesting thing about this theorem is that the proof to it could be done probabilistically, where we consider some certain particular events, and we realize that the Riemann zeta series sum is actually equivalent to finding a certain intersection of infinitely many independent events. And first it is just an infinite product of certain events. And first we have the Riemann zeta function equalling a particular infinite product. And I think that is something that is really out of out of our imagination, because not only does it link two things—a sum to an infinite product, but at the same time, the way that it proves it comes from somewhere we could not even imagine, which is from probability. So if I need to pair this theorem with something, I would say it’s like a spider web, because you can see that there's very intricate connections and that things connect to each other, but in the most mysterious ways.

ELL: Cool. Well, thanks.

TT: Thank you.

Courtney Davis: So Hi, I'm Courtney Davis. I am an associate professor at Pepperdine University out in LA.

EL: Okay. And I hear that we have a favorite model, not a favorite theorem from you.

CD: Yes. So I'm a math biologist. So I'm going to say the obvious one, which is SIR modeling, because it is the entry way into getting to do this cool stuff. It’s the way that I get to show students how to write models. It's the first model I ever saw that had biology in it. And it's something that is ubiquitous and used widely. And so despite being the first thing everyone learns, it's still the first thing everyone learns. And that's what makes it interesting to me.

EL: Yeah. And and can you kind of just sum up in a couple sentences what this model is, what SIR means?

CD: Yeah. So SIR is you are modeling the spread of disease through a susceptible (S) population through infected and into recovered or immune, and you can change that up quite a lot. There are a lot of different ways to do it. It's not one fixed model. And it's all founded on the very simple premise that when two individuals run into each other in a population, that looks like multiplication. And so you can take multiplication, and with that build all the interactions that you really need, in order to capture what's actually happening in a population that at least is well mixed, so that you have a big room of people moving around about it, for instance.

EL: Okay. And I'm going to spring something on you, which is that usually we pair something with our theorem, or in this case model, so we have our guests, you know, choose a food, beverage, piece of art, or anything. Is there anything that you would suggest that pairs well with SIR?

CD: With an SIR model, I would say, a paint gun.

EL: Okay.

CD: I don't know that that's what you're looking for.

EL: That’s great.

CD: Simply because running around and doing pandemic games or other such things is also a common way to get data on college campuses so that you can introduce students, and they can parameterize their models by paint guns or water guns or something like that.

EL: Oh, cool. I like it. Thank you.

CD: Absolutely. Thank you.

Jenny Kenkel: I’m Jenny Kenkel. I'm a graduate student at the University of Utah. I study commutative algebra. My favorite theorem is this isomorphism between a particular local cohomology module and an injective module: The top local cohomology of a Gorenstein ring is isomorphic to the injective hull of its residue field. But I was thinking that maybe it would pair really well with like, a dark chocolate and a sharp cheddar, because these two things are isomorphic, and you would never expect that. But then they go really well together, just in the same way that I think a dark chocolate and a sharp cheddar seem kind of like a weird pairing, but then it's amazing. Also, they're both beautiful.

EL: Nice, thank you.

JK: Thank you.

Dan Daly: My name is Dan Daly. And I am the interim chair of the Department of Mathematics at Southeast Missouri State University.

KK: Southeast—is that in the boot?

DD: That is close to the boot heel. It's about two hours south of St. Louis.

KK: Okay. I'm a Cardinals fan. So I'm ready, we’ve got something here. So what's your favorite theorem?

DD: So my favorite theorem is actually the classification of finite simple groups.

KK: That’s a big theorem.

DD: That is a very big, big,

KK: Like 10,000 pages of theorem.

DD: At least

KK: Yeah. So what draws you to this? Is it your area?

DD: So I am interested in algebraic and combinatorics, and I am generally interested in all things related to permutations.

KK: Okay.

DD: And one of the things that drew me to this theorem is that it's such an amazing, collaborative effort and one of the landmarks of 20th century mathematics.

KK: Big deal. Yeah.

DD: And, you know, it just to me, it seems such a such an amazing result that we can classify these building blocks of finite groups.

KK: Right. So what does one pair this with?

DD: So I think since it's such a collaborative effort, I'm going to pair it with Louvre museum.

KK: The Louvre, okay.

DD: Because it's a collection of all of these different results that are paired together to create something that is really, truly one of a kind.

KK: I’ve never been. Have you?

DD: I have. It’s a wonderful place. Yeah. It’s a fabulous place. One of my favorite places.

KK: I’m going to wait until I can afford to rent it out like Beyonce and Jay Z.

DD: Yeah, right.

KK: All right, well thanks, Dan. Enjoy your time at the Joint Math Meetings.

DD: All right, thank you much.

Charlie Cunningham: My name's Charlie Cunningham. I'm visiting assistant professor at Haverford College. And my area of research originally is, or still is, geometric group theory. But the theorem that I want to talk about was a little bit closer to set theory, which is I want to talk about the existence of solutions to Cauchy’s functional equation.

EL: Okay. And what is Cauchy’s functional equation?

CC: So Cauchy’s functional equation is a really basic sort of thing you can ask about a function. It's asking, all right, you take the real numbers, and you ask is there—what are the functions from the real numbers to the real numbers where if you add two numbers together, and then apply the function, it's the same thing as applying the function to both of those numbers and then adding them together?

EL: Okay. So kind of like you're naive student and wanting to—how a function should behave.

CC: Yes. Right. So this would come up in a couple of places. So if you’ve taken linear algebra, that's the first axiom of a linear function. It doesn't ask about the scaling part. It's just the additive part. And if you've done group theory, it's a fancy way, is it's all the homomorphisms from the real numbers to themselves, an additive group. So the theorem basically, is that well, well, first of all, the question is, well, there are some obvious ones. There are all the functions where you just multiply by a fixed number, all the linear functions you’d know from linear algebra, like 2 times x, 3 times x, or π times x, any real number times x. So the question is, are there any others? Or are those the only functions that exists at all that satisfy this equation? And the theorem turns out that the answer depends on the fundamental axioms you take for mathematics.

EL: Wow. Okay.

CC: Right. So the answer is just to use a little bit of set theory, that if you are working in a set theory, which most mathematicians do, that has something called the axiom of choice in it, then the answer is no, there are lots and lots and lots of other functions that satisfy this equation, other than those obvious ones, but they're almost impossible to think about or write down. They're not continuous anywhere, they are not differentiable anywhere. They're not measurable, if anyone knows what that means. Their graph, if you tried to draw them, are dense in the entire plane, which means any little circle you draw on the plane intersects of the graph somewhere. They still pass the vertical line test. They’re still functions that are well-defined. And I really like this theorem. One reason is because it's a really great place for math students to learn that there isn't always one right answer in math. Sometimes the answer to very reasonably posed questions isn't true or false. It depends on the fundamental universe we’re working in. It depends on the what we all sit down and agree are the starting rules of our system. And it's a sort of question where you wouldn't realize that those sorts of considerations would come up. It also comes up—When I've asked linear algebra students, it's equivalent to the statement are both parts of the definition of a linear function actually necessary? We usually give them to you as two pieces: one, it satisfies this, and the other is scalars pull out. Do we actually need that second part? Can we prove that scalars pull out just from the first part? And this is the only way to prove the answer's no. It's a good exercise to try yourself to prove just from this axiom, that rational scalars pull out, any rational number has to pull out of that function. But real numbers, not necessarily. And these are the counter examples. So it's a good place at that level when you're first learning math, to realize that there are really subtle issues of what we really think truth means when we're beginning to have these conversations

EL: Nice. And what is your theorem pairing?

CC: My theorem pairing, I'm going to pair it with artichokes.

EL: Okay.

CC: I think that artichokes also had a bad rap for a lot of time, for a long time. You should also look at the artichoke war, if you've never heard of it, a great piece of history of New York City, and it took a long time for people to really understand that these prickly, weird looking vegetables can actually be delicious if approached from the right perspective.

EL: Nice. Well, thank you.

Ellie Dannenburg: So I'm Ellie Dannenberg, and I am visiting assistant professor at Pomona College in Claremont, California. And my favorite theorem is the Koebe-Andreev-Thurston circle packing theorem, which says that if you give me a triangulation of a surface, that I can find you exactly one circle packing where the vertices of your triangulation correspond to circles, and an edge between two vertices says that those circles are tangent.

EL: Okay, so this seems site kind of related to Voronoi things? Maybe I'm totally going in a wrong direction.

ED: So, I know that these are—so I don't think they're exactly related.

EL: Okay. Nevermind. Continue!

ED: Okay. But, right, it’s cool because the theorem says you can find a circle packing if I hand you a triangulation. But what is more exciting is you can only find one. So that's it.

EL: Oh, huh. Cool. All right. And do you have something that you would like to pair with this theorem?

ED: So I will pair this theorem with muhammara, which is this excellent Middle Eastern dip made from walnuts and red peppers and pomegranate molasses that is delicious and goes well with anything.

EL: Okay. Well, it's a good pairing. My husband makes a very good version. Yeah. Thank you.

ED: Thank you.

Manuel González Villa: This is Manuel González Villa. I'm a researcher in CIMAT [Centro de Investigación en Matemáticas] in Guanajuato, Mexico, and my favorite theorem is the Newton-Puiseux theorem. This is a generalization of implicit function theorem but for singular points of algebraic curves. That means you can parameterize a neighborhood of a singular point on an algebraic curve with a power series expansion, but with rational exponents, and the denominators of those exponents are bounded. The amazing thing about this theorem is that it’s very old. It comes back from Newton. But some people will still use it in research. I learned this theorem in Madrid where I made my PhD from a professor call Antonia Díaz-Cano. And also I learned with the topologist José María Montesinos to apply this theorem. It has some high-dimensional generalizations for some type of singularities, which are called quasi-ordinary.

The exponents—so you get a power series, so you get an infinite number of exponents. But there is a finite subset of those exponents which are the important ones, because they codify all the topology around the singular point of the algebraic curve. And this is why this theorem is very important. And the book I learned it from is Robert Walker’s Algebraic Curves. And if you want a more recent reference, I recommend you to look at Eduardo Casas-Alvero’s book on singularities of plane curves. Thank you very much.

EL: Okay.

EL: Yeah. So can you introduce yourself?

JoAnne Growney: My name is JoAnne Growney. I'm a retired math professor and a poet.

EL: And what is your favorite theorem?

JG: Well, the last talk I went to has had me debating about it. What I was prepared to say an hour ago was that it was the proof by contradiction that the real numbers are countable, and Cantor's diagonal proof. I like proofs by contradiction because I kind of like to think that way: on the one hand, and then the opposite. But I just returned from listening to a program on math and art. And I thought, wow, the Pythagorean theorem is something that I use every day. And maybe I'm being unfair to take something about infinity instead of something practical, but I like both of them.

EL: Okay, so we've got a tie there. And have you chosen something to pair with either of your theorems? We like to do, like, a wine and food pairing or, you know, but with theorems, you know, is there something that you think goes especially well, for example a poem, if you’ve got one.

JG: Well, actually, I was thinking of—the Pythagorean theorem, and it's probably a sound thing, made me think of a carrot.

EL: Okay.

JG: And oh, the theorem about infinity, it truly should make me think of a poem, but I don't have a pairing in mind.

EL: Okay. Well, thank you.

JG: Thank you.

Mikael Vejdemo-Johansson: I’m Michael Vejdemo-Johansson. I'm from the City University of New York.

KK: City University of New York. Which one?

MVJ: College of Staten Island and the Graduate Center.

KK: Excellent. All right, so we're sitting in an Afghan restaurant at the JMM. And what is your favorite theorem?

MVJ: My favorite theorem is the nerve lemma.

KK: Okay, so remind everyone what this is.

MVJ: So the nerve lemma says—well, it’s basically a family of theorems, but the original one as I understand it says that if you have a covering of a topological space where all the cover elements and all arbitrary intersections of cover elements are simple enough, then the intersection complex, the nerve complex of the covering that inserts a simplex for each nonlinear intersection is homotopy equivalent to the whole space.

KK: Right. This is extremely important in topology.

MVJ: It fuels most of topological data analysis one way or another.

KK: Absolutely. Very important theorem. So what pairs well, with the nerve lemma?

MVJ: I’m going to go with cotton candy.

KK: Cotton candy. Okay, why is that?

MVJ: Because the way that you end up collapsing a large and fluffy cloud of sugar into just thick, chewy fibers if you handle it right.

KK: That's right. Okay. Right. This pairing makes total sense to me. Of course, I’m a topologist, so that helps. Thanks for joining us, Mikael.

MVJ: Thank you for having me.

Michelle Manes: I’m Michelle Manes. I'm a professor at the University of Hawaii. And my favorite theorem is Sharkovskii’s theorem, which is sometimes called period three implies chaos. So the statement is very simple. You have a weird ordering of the natural numbers. So 3 is bigger than 5 is bigger than 7 is bigger than 9, etc, all the odd numbers. And then those are all bigger than 2 times 3 is bigger than 2 times 5 is bigger than 2 times 7, etc. And then down a row 4 times every odd number, and you get the idea. And then everything with an odd factor is bigger than every power of 2. And the powers of 2 are listed in decreasing order. So 23 is bigger than 22 is bigger than 2 is bigger than 1.

EL: Okay.

MM: So 1 is the smallest, 3 is the biggest, and you have this big weird array. And the statement says that if you have a continuous function on the real line, and it has a point of period n, for n somewhere in the Sharkovskii ordering, so put your finger down on n, it’s got a point of period everything less than n in that ordering. So in particular, if it has a point of period 3, it has points of every period, every integer. So I mean, I like the theorem, because the hypothesis is remarkable. The hypothesis is continuity. It's so minimal.

EL: Yeah.

MM: And you have this crazy ordering. And the conclusion is so strong. And the proof is just really lovely. It basically uses the intermediate value theorem and pretty pictures of folding the real line back on itself and things like that.

EL: Oh, cool.

MM: So yeah, it's my favorite theorem. Absolutely.

EL: Okay. And do you have something that you would suggest pairing with this theorem?

MM: So for me, because when I think of the theorem, I think of the proof of it, which involves this, like stretching and wrapping and stretching and wrapping, and an intermediate value theorem, it feels very kinetic to me. And so I feel like it pairs with one of these kind of moving sculptures that moves in the wind, where things sort of flow around.

EL: Oh, nice.

MM: Yeah, it feels like a kinetic theorem to me. So I'm going to start with the kinetic sculpture.

EL: Okay. Thank you.

MM: Thanks.

John Cobb: Hey there, I’m John Cobb, and I'm going to tell you my favorite theorem.

EL: Yeah. And where are you?

JC: I’m at College of Charleston applying for PhD programs right now.

EL: Okay.

JC: Okay. So I picked one I thought was really important, and I'm surprised it isn't on the podcast already. I have to say it's Gödel’s incompleteness theorems. Partly because for personal reasons. I'm in a logic class right now regarding the mechanics of the actual proof. But when I heard it, I was becoming aware of the power of mathematics, and hearing the power of math to talk about its own limitations, mathematics about mathematics, was something that really solidified my journey into math.

EL: And so what have you chosen to pair with your theorems?

JC: Yeah, I was unprepared for this question. So I’m making up on the spot.

EL: So you would say your your preparation was…incomplete?

JC: [laughing] I would say that! Man. I'll go with the crowd favorite pizza for no reason in particular.

EL: Well pizza is the best food and it's good with everything.

JC: Yeah.

EL: So that's a reason enough.

JC: Awesome. Well, thank you for the opportunity.

EL: Yeah, thanks.

Talia Fernós: My name is Talia Fernós, and I'm an associate professor at the University of North Carolina at Greensboro. My favorite theorem is Riemann’s rearrangement theorem. And basically, what it says is that if you have a conditionally convergent series, you can rearrange the terms in the series that the series converges to your favorite number.

EL: Oh, yeah. Okay, when you said the name of it earlier, I didn't remember, I didn't know that was the name of the theorem. But yes, that's a great theorem!

TF: Yeah. So the proof basically goes as follows. So if you do this with, for example, the series which is 1/n times -1 to, say, the n+1, so that looks like 1-1/2+1/3-1/4, and so on. So when you try to see why this is itself convergent, what you'll see is that you jump forward 1, then back a half, and then forward a third, back a fourth, so if you kind of draw this on the board, you get this spiral. And you see that it very quickly, kind of zooms in or spirals into whatever the limit is.

So now, this is conditionally convergent, because if you sum just 1/n, this diverges. And you can use the integral test to show that. So now, if you have a conditionally convergent series, you will have necessarily that it has infinitely many positive terms and infinitely many negative terms. And that each of those series independently also diverge. So when you want to show that a rearrangement is possible, so that it converges to your favorite number, what you're going to do is, let's say that you're trying to make this converge to 1, okay? So you're going to add up as many positive terms as necessary, until you overshoot 1, and then as many negative terms as necessary until you undershoot, and you continue in this way until you kind of have again, this spiraling effect into 1. And now the reason why this does converge is that the fact that it's conditionally convergent also tells you that the terms go to zero. So you can add sort of smaller and smaller things.

EL: Yeah, and you you don't run out of things to use.

TF: Right.

EL: Yeah. Cool. And what have you chosen to pair with this theorem?

F: For its spiraling behavior, escargot, which I don't eat.

EL: Yeah, I have eaten it. I don't seek it out necessarily. But it is very spiraly.

TF: Okay. What does it taste like?

EL: It tastes like butter and parsley.

TF: Okay. Whatever it’s cooked in.

EL: Basically. It's a little chewy. It's not unpleasant. I don't find a terribly unpleasant, but I don’t

TF: think it's a delicacy.

EL: Yeah. But I'm not very French. So I guess that's fair. Well, thanks.

TF: Sure.

This episode of my favorite theorem is a whirlwind of “flash favorite theorems” we recorded at the Joint Mathematics Meetings in Baltimore in January 2019. We had 16 guests, so we’ll keep this brief. Below is a list of our guests and their theorems with timestamps for each guest in case you want to skip around in the episode. We hope you enjoy this festival of theorem love as much as we enjoyed talking to all of these mathematicians!