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    Mathematics

    My Favorite Theorem

    Join us as we spend each episode talking with a mathematical professional about their favorite result. And since the best things in life come in pairs, find out what our guest thinks pairs best with their theorem.

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    Copyright: © Kevin Knudson & Evelyn Lamb

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    Latest Episodes:
    Episode 15 - Federico Ardila Mar 22, 2018
    Show notes

    Episode 15 - Federico Ardila Kevin Knudson & Evelyn Lamb Download Evelyn Lamb: Welcome to My Favorite Theorem. I'm your host Evelyn Lamb, a freelance math and science writer in Salt Lake City, Utah, and this is your cohost. Kevin Knudson: I'm Kevin Knudson, professor of mathematics at the University of Florida. How are you doing, Evelyn? EL: I am still on an eclipse high. On Monday, a friend and I got up, well got up in time to get going by 5 in the morning, to get up to Idaho and got to experience a total eclipse, which really lived up to the hype. KK: You got totality? EL: Yes, we got in the band of totality for a little over two minutes. KK: We had 90 percent totality. It was still pretty impressive. Our astronomy department here set up their telescopes. We have a great astronomy department here. They had the filters on. There were probably 500 kids in line to see the eclipse. It was really pretty spectacular. EL: It was pretty cool. I'm already making plans to go visit my parents on April 8, 2024 because they're in Dallas, which is in the path for that one. KK: Very nice. EL: So I've been trying to get some work done this week, but then I just keep going and looking at my friends' pictures of the eclipse, and NASA's pictures and everything. I'm sure I will get over that at some point. KK: It was the first day of classes here for the eclipse. It was a bit disruptive, but in a good way. EL: My spouse also had his first day of class, so he couldn't come with us. KK: Too bad. EL: But anyway, we are not here to talk about my feels about the eclipse. We are here to welcome Federico Ardila to the podcast. So Federico, would you like to say a bit about yourself? Federico Ardila: Yeah, first of all, thanks so much for having me. As Evelyn just said, my name is Federico Ardila. I never quite know how to introduce myself. I'm a mathematician, I'm a DJ, I'm an immigrant from Colombia to the US, and I guess most relevant to the podcast, I'm a math professor at San Francisco state university. I also have an adjunct position in Colombia at theUniversidad de los Andes. I'm also spending the semester at MSRI [Mathematical Sciences Research Institute] in Berkeley as a research professor, so that's what I'm up to these days. KK: I love MSRI. I love it over there. I spent a semester there, and every day at teatime, you walk into the lounge and get the full panoramic view of the bay. You can watch the fog roll in through the gate. It's really spectacular. FA: Yeah, you know, one tricky thing is you kind of want to stay for the sunset because it's so beautiful, but then you end up staying really late at work because of it. It's a balance, I guess. KK: So, the point of this thing is that someone has a favorite theorem, so I actually don't know what your favorite theorem is, so I'm going to be surprised. What's your favorite theorem, Federico? FA: Yeah, so first of all I apologize for not following your directions, but it was deliberate. You both asked me to tell you my favorite theorem ahead of time, but I'm not very good at following directions. But I also thought that since I want to talk about something that I think not a lot of people think about, maybe I shouldn't give you a heads-up so we can talk about it, and you can interrupt me with any questions that you have. EL: Get our real-time reactions here. FA: Exactly. The other thing is that instead of talking about a favorite theorem, I want to talk about a favorite object. There's a theorem related to it, but more than the theorem, what I really like is the object. EL: Okay. FA: I want to talk a little about matroid theory. How much do you two think about matroids? KK: I don't think about them much. EL: Not at all. KK: I used to know what a matroid is, so remind us. FA: Excellent. Yeah, so matroid theory was basically an abstraction of the notion of independence. So something that was developed by Hassler Whitney, George Birkhoff, and Saunders MacLane in the '30s. Back then, you could write a thesis in graph theory at Harvard. This was part of Hassler Whitney's Ph.D. thesis where he was trying to solve the four-color theorem, which basically says that if you want to color the countries in a map, and you only have four colors, you will always be able to do that in such a way that no two neighboring countries are going to have the same color. So this was one of the big open problems at the time. At the time they were trying to figure out a more mathematical grounding or structure that they could put on graphs, and so out of that the theory of matroids was born. This was in a paper of Whitney in 1935, and he had the realization that the properties that graphs have with regards to how graphs cycle around, what the cycles are, what the spanning trees are, and so on, are exactly the same properties that vectors have. So there was a very strong link between graph theory and linear algebra, and he basically tried to pursue an axiomatization of what was the key combinatorial essence of independence? EL: Okay, and so by independence, is that like we would think of linear independence in a matrix? Matroid and matrix are kind of suggestively similarly named. So is that the right thing we should be thinking about for independence? FA: Exactly, so you might think that you have a finite set of vectors in a vector space, and now you want to figure out the linear dependencies between them. And actually that information is what's called the matroid. Basically you're saying these two vectors are aligned, or these three vectors lie on the same plane. So that information is called the matroid, and Whitney basically laid out some axioms for what the kind of combinatorial properties that linear independence has, and what he realizes is that these are exactly the same axioms that graphs have when you think about independence. Now you need a new notion of independence. In a graph you're going to say you have a dependency in edges whenever they form a cycle. So somehow it is redundant to be able to walk from point A to point B in two different ways, so whenever there is that redundancy, we call it dependency in a graph. Basically Whitney that these were the same kind of properties, and he defined a matrix to be an abstract mathematical object that was supposed to capture that notion of independence. EL: Okay. So this is very new to me, so I'm just kind of doing free association here. So I'm familiar with the adjacency matrix of a graph. Does this contain information about the matroid, or is this a little side path that is not really the same thing? FA: This is a really good point. To every graph you can associate an adjacency matrix. Basically what you do is if you have an edge from vertex i to vertex j in the graph, in the matrix you put a column that has a bunch of 0's with a 1 in position i and a -1 in position j. You might think of this as the vector ei-ej where the e's are the standard basis in your vector space. And you're absolutely right, Evelyn, that when you look at the combinatorial dependencies between the graph in terms of graph dependence, they're exactly the linear dependencies in that set of vectors, so in that sense, that vector perfectly models the graph as matroid theory is concerned. EL: Okay. FA: So, yeah, that's a really good comparison. One reason that I love matroids is that it turns out that they actually apply in a lot of other different settings. There are many different notions of independence in mathematics, and it was realized over the years that they also satisfy these properties. Another notion of independence that you might be familiar with is the notion of algebraic independence. You learn this in a course in field extensions, and you learn about extension degrees and transcendence bases and things like this. That's the notion of algebraic independence, and it turns out that that notion of independence also satisfies these axioms that Whitney laid out, and so they also form a matroid. So whenever you have a field extension, you also have a matroid. KK: So what's the data you present? Say X is a matroid. If you're trying to write this down, what gets handed to you? FA: That's another really good question, and I think it's a bit of a frustrating question because it depends on who you ask. The reason for this is that so many people encounter matroids in their everyday objects that they think of them in very different ways. Some people, if they hand you a matroid, they're going to give you a bunch of sets. Maybe this is the most common things. If you give me a list of vectors, then I could give you the linearly independent sets out of these sets of vectors. That would be a list, say 1 and 2 are independent, 1 and 4 are independent, 1, 6, and 7 are dependent, and so on. That would be a set system. If you asked somebody else, then they might think of that as a simplicial complex, and they might hand you a simplicial complex and say that's a matroid. One thing that Birkhoff realized, and this was very fashionable in the '30s at Harvard, is to think about lattices in the sense of posets. If you had Birkhoff, he would actually hand you a lattice and say that's a matroid. I think this is something that's a bit frustrating for people that are trying to learn matroids. I think there are at least 10 different definitions of what a matroid is, and they're all equivalent to each other. Actually Rota made up the name cryptomorphism. You have the same theory, and you have two different axiom systems for the same theory, and you need to prove they're equivalent. This is something that when I first learned about matroids, I hated it. I found it really frustrating. But I think as you work in this topic, you realize that it's very useful to have the insight someone in linear algebra would have, the insight somebody in graph theory would have, the insight that somebody in algebraic geometry would have. And so to do that, you end up kind of going back and forth between these different ways of presenting a matroid. EL: Like the clothing that the matroid is wearing at the time. Which outfit do you prefer? FA: Absolutely. KK: Being a good algebraic topologist, I want to say that this sort of reminds me of category theory. Can you describe these things as a functor from something to something else? It sort of sounds like you've got these sort of structures that are preserved, they're all the same, or they're cryptomorphic, right? So there must be something, you've got a category of something and another different category, and the matroid is sort of this functor that shows a realization between them, or am I just making stuff up? FA: I should admit that I'm not a topologist, so I don't think a lot about categories, but I definitely do agree that over the last few years, one program has been to set down stronger algebraic foundations, and there's definitely a program of categorizing matroids. I'm not sure what you're saying is exactly correct. KK: I'm sure it isn't. FA: But that kind of philosophy is at play here. KK: So you mentioned that there was a theorem lurking behind your love of matroids. FA: So let me first mention one quick application, and then I'll tell you what the object is that I really like. There's another application of this to matching problems. One example that I think academic mathematicians are very familiar with is the problem of matching job candidates and positions. It's a very difficult problem. Here you have a notion of dependences; for example, if the same person is offered two different jobs, they can only take one of those jobs, so in that sense, those two jobs kind of depend on each other. It turns out that this setting also provides a matroid. One reason that that is important is it's a much more applied situation because, you know, there are many situations in real life where you really need to do matchings, and you need to do it quickly and inexpensively and so on. Now when this kind of combinatorial optimization community got a hold of these ideas, and they wanted to find a cheap matching quickly, then one thing that people do in optimization a lot is if you want to optimize something, you make a polytope out of it. And so this is the object that I really like and want to tell you about. This is called the matroid polytope. EL: Okay. FA: Out of all these twelve different sets of clothing that matroids like to wear, my favorite outfit is the matroid polytope. Maybe I'll tell you first in the abstract why I like this so much. EL: First, can we say exactly what a polytope is? So, are we thinking a collection of vertices, edges, faces, and higher-dimensional things because this polytope might live in a high-dimensional space? Is that what we mean? FA: Exactly. If your polytope is in two dimensions, it's a polygon. If it's in three dimensions, it's the usual solids that we're used to, like cubes, pyramids, and prisms, and they should have flat edges, so they should have vertices, edges, and faces like you said. And then the polytope is just the higher-dimensional generalization for that. This is something that in combinatorial optimization is very natural. They really need these higher-dimensional polytopes because if you have to match ten different jobs, you have ten different axes you have to consider, so you get a polytope in ten dimensions. KK: Sort of the simultaneous, feasible regions for multiple linear inequalities, right? FA: Exactly. But yeah, I think Edmonds was the first person who said, okay, I want to study matroids. I'm going to make a polytope out of them. Then one thing that they realized is there is a notion in algorithms of greedy algorithms, which is, a greedy algorithm is when you're trying to accomplish a task quickly, what you do is you just, at each point in time, you just do the thing that seems best at the time. If we go back to the situation of matching jobs, then the first thing you might say is ask one school, okay, what do you want? And then they would hire the first person, and they would choose a person, and then you'd ask the next school, what do you want, and they would choose the next best person, and so on. We know that this strategy doesn't usually work. This is the no long-term planning solution. You just do what immediately what seems best to do, and what the community realized was that matroids are exactly where greedy strategies work. That's another way of thinking of matroids is that's where the greedy algorithm works. And the way they proved this was with this polytope. So for optimization people, there's this polytope. It turns out that this polytope also arises in several other settings. There's a beautiful paper of Gelfand, Goresky, MacPherson, and and Serganova, and they're doing algebraic geometry. They're studying toric varieties. You don't need to know too much about what this is, but the main point is that if you have a toric variety, there is a polytope associated to it. There's something called the moment map that picks up a toric variety and takes it to a polytope. In this very different setting of toric varieties, they encounter the same polytope, coming from algebraic geometry. Also there's a third way of seeing this polytope coming from commutative algebra. If you have an ideal in a polynomial ring, and again it's not too important that you know exactly what this means, but there's a recipe, given an ideal, to get a polytope out of it. Again, there's a very natural way that, given a very natural ideal, you get the same polytope, coming from commutative algebr…

    Full show notes at the publisher

    Episode 14 - Laura Taalman Mar 08, 2018
    Show notes

    Episode 14 - Laura Taalman Kevin Knudson & Evelyn Lamb Download Kevin Knudson: Welcome to My Favorite Theorem. I’m your host, professor of mathematics at the University of Florida Kevin Knudson. This is my cohost. Evelyn Lamb: Hi! I’m Evelyn Lamb, a math and science writer in Salt Lake City, Utah. Yeah, things are going well here. I went to the mall the other day, and I was leaving—I had to go to get my computer repaired, and I was in a bad mood and stuff, and I was leaving, and there was just, I walked into the parking lot, there was this beautiful view of this mountain. It’s a mall I don’t normally go to, and these mountains: Wow, it’s amazing that I live here. KK: Is this the picture you put on Twitter? EL: Yeah, or Facebook. KK: Yeah, that is pretty spectacular. Well, I had a haircut today, that’s all I can say. Anyway, let’s get to it. We are very pleased in this episode to welcome Laura Taalman. Laura, do you want to introduce yourself and tell people about yourself? Laura Taalman: Sure. Hi, thank you for having me on this podcast. I am extremely excited to be on it. Thank you. EL: We’re glad you’re here. LT: I’m a math professor at James Madison University, which is in Virginia. I’ve been here since 2000. We don’t have graduate students in our department, we only have undergraduate students. So when I got here, straight out of grad school, I had been studying singular algebraic geometry, and I just could not talk about that with students when we were doing undergraduate research. And I switched to knot theory. I’ve since switched to many things. I seem to switch to a new hat every year or so. My new hat is 3D printing. I’ve been doing a lot with mathematical 3D printing, but I think I’m still wearing that math jacket while I’m wearing the 3D printing hat. EL: That’s a very exciting costume. LT: Yes, it’s a very exciting costume, that’s true. KK: And for a while you were the mathematician in residence at the National Museum of Mathematics, right? LT: MoMath, that’s true. I did a semester at that, and that was the start of me living in New York City for a couple years to solve a two-body problem. I spent a couple years working in industry in 3D printing there. I just recently, last year, came back to the university. I now have the jacket and hat problem. KK: Well, that’s better than the two-body problem. LT: It’s better than not having a jacket or a hat. KK: That too, right. So actually I was just visiting James Madison a couple of months ago. Laura’s department was very nice. Actually, my wife was visiting, and I was just tagging along, so I crashed their colloquium and just gave one. And everybody was really nice. I really, you know, I went to college at Virginia Tech two hours down the road. I’d never really spent any time in Harrisonburg, but it’s a lovely little town. LT: It is. KK: It’s very diverse. I had lunch at an Indonesian place. EL: Oh wow. KK: It was fantastic. I can’t get that here, you know. LT: It’s an amazing place. KK: It is. I thought it was really great. Anyway, so, you’re going to tell us about your favorite theorem. You told us once beforehand, but I’ve kind of forgotten. I remember, but this is pretty great. So Laura, what’s your favorite theorem? LT: My favorite theorem comes from my knot theory phase. It’s a theorem in knot theory. I don’t know how much knot theory I should assume before saying what this theorem is, but maybe I should just set it up a little bit. KK: Yeah, set it up a little bit. EL: That would be great. LT: In knot theory, you’re in studying, say, you tie a shoelace and you connect the ends, and you do that again with a different piece of string, and you’re wondering if these could possibly be the same knot in disguise, like you could deform one to another. Of course, we don’t study knots in three dimensions like that because no one can draw that. This is, in fact, how I got into 3D printing was trying to print three-dimensional versions of knots that I could look at their conformations. KK: Very cool. LT: But really mathematicians study knots as planar diagrams. You’ve got a diagram of a knot with crossings: over crossings and under crossings, a collections of arcs in the plane with crossings. A very old result in knot theory is that if two of those diagrams represent the same knot secretly (they might look very different), there is a sequence of what are known as Reidemeister moves that gets from one to the other. Reidemeister moves are super simple moves, like putting a twist in a strand or moving one strand over another strand, or moving a strand over or under a crossing, right? Super simple. It’s been proved that that’s sufficient, that’s all you need to change one diagram into any other equivalent diagram. KK: OK. LT: So my favorite theorem is by Joel Haas and Jeffrey Lagarias, I think is his name. Haas is from UC Davis, and Lagarias is at Michigan. And in 2001, they proved an upper bound for the number of Reidemeister of moves that it takes to turn a knot diagram that’s secretly unknotted and turn it into basically a circle, the unknot. So they wanted to answer this question. We know we can, if it’s unknotted, turn it into a circle. The question is how many of these Reidemeister moves are you going to need, and even worse than that, if you start with a diagram that has, like, 10 crossings, you might actually have to increase the number of crossings along the way while simplifying the knot. It’s not necessarily true that the number of crossings will be monotonically decreasing throughout the Reidemeister move process. You might increase the number, you might have to increase the number of crossings by a lot. So this is a nontrivial question of how many Reidemeister moves. So they said, OK, look. We want to find this one constant that will give you an upper bound for any knot that’s trivial to unknot it, the number of Reidemeister moves, and they said that the bound would be of the form 2 times [ed note: Taalman misspoke here and meant to the power instead of times, as is clear from the rest of the conversation] a constant times n, where n is the number of crossings. So if it’s a 10-crossing knot, it would be like 2^10 times this constant, right? KK: OK. LT: I was playing around with some numbers, so for example, if you had a 6-crossing knot, right, and if the constant happened to be 10, this would be 2^60, which is over a quintillion. KK: That’s a lot. LT: If that constant were 10, and your knot started out with just 6 crossings, that’s a big number. But that is not the bound that they found. KK: It’s not 10. LT: Their theorem, my favorite theorem, is that they came up with a bound that the maximum number of Reidemeister moves that would be needed to unknot a trivial knot, that constant is 2^10^11 times n. The constant is 10^11, so 2^(10^11) times n. So I put this into Wolfram Alpha with n=6. So say you have a 6-crossing knot. It’s not so bad. I put in 2^10million [ed note: Taalman misspoke here and meant hundred billion; 10^7 or 10 million comes up as a bound in a different part of the paper], and then also times 6 in the exponent. I just did this this afternoon, and do you know what Wolfram Alpha said? KK: It couldn’t do it? LT: I’ve never seen this. It said nothing. EL: You broke it? LT: It didn’t spin and think about it, and it didn’t attempt to say something. It literally just pretended that I did not press the button. This is really a big number. KK: I’m surprised. You know what it should have done? It should have given you the shrug emoji. LT: Yeah, that would be great if it had that. That would be perfect. So the reason it’s my favorite theorem, I guess there are a lot of reasons, but the primary reason is: this is ridiculous, right? If you have a 6-crossing knot, there’s no way you’re going to need even a quintillion Reidemeister moves in reality. If I actually give you a 6-crossing knot in reality, you’re not going to need a quintillion Reidemeister moves, let alone this number of silence that Wolfram Alpha can’t even calculate. So to me, it’s just really funny. And I could talk a little more about that. But it’s an important result because it’s the first upper bound, which is great, but also, it’s just, it’s ridiculous. KK: It’s clearly not sharp. They didn’t cook up an example. LT: It’s clearly not sharp. KK: They didn’t cook up an example where they had to use that many moves. LT: Right, no, they did not. It’s kind of like what happened with the twin prime conjecture, and people online were looking at the largest gap you could guarantee, I don’t know if I’m going to say this right, the largest gap. KK: Right, it was 70 million. LT: And eventually primes would have to appear with that gap. That gap started out being huge, I don’t remember what it was, but it was really big, and it ended up getting better and better and better and better. KK: Right. LT: So this is like the first shot in that game for Reidemeister moves, is 2 to the 10 to the 11th times the number of crossings. KK: Has anybody made that better yet? LT: They have. So that was in 2001, this exponential upper bound with very large exponent, and in 2011, two different mathematicians, Coward and Lackenby, I think, proved a different bound that involved an exponential tower. That gives you an idea of just how big that first bound was, if this bound is an exponential tower. EL: And it’s better? LT: Actually, let me say that slightly differently because this is not necessarily better. Their result was actually a little bit different. Their result wasn’t taking a knot to the unknot. It was taking any knot to any other knot it was equivalent to. KK: OK. EL: OK. LT: This could well be worse, actually. And to tell you the truth, I was not entirely certain how to type this number into Mathematica, into Wolfram Alpha. It could be a lot worse. Their bound for the maximum number of Reidemeister moves that you need to take one knot to another knot that it’s ambient isotopy equivalent to in 3-space, if you had that knot. I’ve got to get my piece of paper to look at this. Their number is what they call exp^c^n(n), so the n is the sum of the crossing numbers of the two knots. The c^n: c is some constant to be determined. It could be laughably large, right? And what exp means is that it’s 2^n iterated that many times. So exp^k, or exp(k)(n) would be 2^n iterated k times. KK: Right. 2 to the 2 to the 2 to the… LT: …2 to the n. So this number is 2 to the 2 to the 2 to the…tower, and the height of this tower is c^n, where n is the number of crossings, and then there’s an n at the top. And the number c is 10 to the one millionth power. KK: Wow. EL: Wow. So this is bad news. LT: This is very bad. So the tower is 10 to the one million high. I’m sure this is worse than the other one. KK: It’s got to be worse. LT: They didn’t try at all to make that low. I did a small example: what if the tower was only length 2 and there was a 6 on the top, so 2^2^6. And you’re doing your brackets from the top down, so 2 to the quantity 2^6. EL: Right. LT: That is over a quintillion. KK: Sure. EL: Yeah, like this is Graham’s number stuff. LT: Yeah, Graham’s number, all that stuff with the arrows. All that stuff with the arrows. EL: Yeah, basically you can’t even tell someone how big Graham’s number is because you don’t have the words to describe the bigness of this number. LT: Yeah, and even with a tower of 2, I’m getting a quintillion. Their length is 10 to the one million. I already don’t understand what 10 to the one million is. KK: No. You know this thing where you pack the known universe with protons, do you know how many there’d be? LT: No. Not many? KK: 10^126. LT: Oh my God. KK: So 10 to the one million. You’ve surely seen Powers of 10, this old Eames movie, right? LT: Yeah, yeah. KK: The known universe just isn’t that big, you know? It’s what, 10 to the 30th across or whatever. It’s nothing. EL: You definitely can’t come up with an example that needs this because the heat death of the universe would occur well before we proved this example needed this many steps. KK: Yeah. LT: I think that these mathematicians know how funny their result it. It’s definitely, it’s not just funny. The proofs are very complicated and have to do with piecewise linear 3-manifolds and all this. I don’t understand the proofs. This is very sophisticated, so I’m not besmirching them by saying it’s funny. But I think they understand how crazy this sounds. They’ll say things like, this Coward-Lackenby paper has a line in there like, notice that this solves the problem of figuring out if two knots are Reidemeister equivalent because all you have to do is look at every sequence of Reidemeister moves of that length, look at them all, and then see if any two of them turn out to be the same knot. Boom, you’ve solved your problem. KK: All you have to do. LT: All you have to do! Problem solved. EL: Yes. LT: Or that, so earlier you asked if the result has been improved upon, and it has, but that wasn’t the reference I wanted to say for that. It has been improved just three years ago by Lackenby, one of the authors of that other result, and their result is polynomial. They found a polynomial bound, not an exponential bound. It’s much better. They found that if n is the number of crossings to go from a trivial knot to the trivial circle, this is back to that problem, it’s 236 times n to the 11th power. KK: OK. LT: It’s not so bad. KK: Right. LT: Not so bad. It is actually pretty bad. But it’s something that Wolfram could calculate. So I did it for example with n equals 3. So say you have a 3-crossing trivial knot. What’s the most number of Reidemeister moves that you would need according to this bound to unknot it? That would be 236 times 3 to the 11th power. That is 2 times 10^31 power, which is 10 nonillion. KK: Right, OK.LT: 10 nonillion. EL: So this isn’t great. LT: But it had a name! Dressed in scientific notation. Positive change. EL: It didn’t cause Wolfram Alpha to run away in fright. LT: No. I think this is the best one so far, this 2014 result by Lackenby. I think it’s the best one. EL: Well that’s interesting, because you know, just for the example of 3, if you try, like, 10 Reidemeister moves, that’s gotta be it. It feels like that has to be so much lower. It’ll be interesting to see if it’s possible to shrink this down more to meet some more realistic bound. LT: Honestly, 3 is a ridiculous example. I used it because it was the smallest, but you’re right. If you think about it, there’s really not that many three-crossing diagrams that one can draw. KK: Right. LT: Of the ones that are trivial, I’m sure you could find a path of Reidemeister moves. This result isn’t made for low-crossing knots, really, I think. Or at least not three. But you’re right, it’s got to be way better than this. KK: This is where mathematicians and computer scientists are never going to see eye to eye on something. A computer scientist will look at this and say, that’s ridiculous. You have not solved the problem. LT: I agree. It’s not good enough. They did have one result in this 2014 paper. Remember I said that you may have to increase the number of crossings? Well back in the original 2001 paper, Haas and Lagarias were like, hey, here’s a fun corollary: you only have to increase the number of crossings by 2 to the power of 10 to the 11th times n at most, because you can’t have more crossings than what it would take for the number of Reidemeister moves. So that’s their corollary. In 2014, that bound is super significantly improved. They just say it’s (7n) squared. That’s not bad at all. They’re saying it doesn’t have to get worse than that on your way to making it the unknot. KK: You might have to go up and down and up and down and up and down, right? LT: Right. I guess then they’re saying the most it would ever have to go up is to that. KK: Yeah. LT: So things are getting better. KK: All the time getting better. So part of the fun of this podc…

    Full show notes at the publisher

    Episode 13 - Patrick Honner Feb 22, 2018
    Show notes Episode 13 - Patrick Honner Kevin Knudson & Evelyn Lamb Download

    Evelyn Lamb: Welcome to My Favorite Theorem. I’m Evelyn Lamb, a freelance math and sci-ence writer in Salt Lake City. And this is my cohost.
    Kevin Knudson: Hi. I’m Kevin Knudson, professor of mathematics at the University of Florida. How are you doing, Evelyn?
    EL: Pretty good. It’s hot here, but it gets cool enough at night that it’s survivable. It’s not too bad.
    KK: It’s just hot here. It’s awful.
    EL: Yeah, there’s really something about that dry heat. I lived in Houston for a while. It’s differ-ent here. So on each episode we invite someone on to tell us about their favorite theorem, and today we’re delighted to have Patrick Honner. Hey! Can you tell us a little bit about yourself?
    Patrick Honner: Hi I’m happy to be here. Great to see you, Evelyn and Kevin. I’m in Brooklyn. It’s hot and muggy here. It’s never survivable in New York. I’ve got that going for me. I’m really excited to be here. I’m a high school math teacher. I teach at Brooklyn Technical High School. I studied math long ago, and I’m excited to talk about my favorite theorem today.
    KK: Cool.
    EL: Great.
    KK: So what do you have for us?
    PH: In thinking about the prompt of what my favorite theorem was, I guess I came to thinking about it from the perspective of a teacher, of course, because that’s what I’ve been doing for the last almost 20 years. So I was thinking about the kinds of theorems I like to teach, that are fun, that I think are really engaging, that are essential to the courses that i teach. A couple came to mind. I teach calculus occasionally, and I think the intermediate value theorem is probably my favorite theorem in calculus. I feel like the mean value theorem gets all the love in calculus. Eve-ryone thinks that’s the most important, but I really like the intermediate value theorem. I really love De Moivre’s theorem as a connection between complex numbers and geometry and alge-bra, and a little bit of group theory in there. But what really stuck out when thinking about what my favorite theorem is was Varignon’s theorem.
    KK: I had to look this up.
    PH: Well I think a lot of people, they know it when you show it to them, but they don’t know the name of it. That’s also part of why I like it. The name is sort of exotic sounding. It transports them to France somehow.
    EL: Nice.
    KK: Varignon’s theorem is a theorem of Euclidean geometry. It’s not that deep or powerful or exciting, but there’s just something about the way you can interact with it and play with it in class, and the way you prove it and the different directions it goes that really makes it one of my favorite theorems.
    KK: Now we’re intrigued.
    EL: Yeah. What is this theorem?
    PH: Imagine, so Varignon’s theorem is a theorem about quadrilaterals. If you imagine a quadrilateral in the plane, you’ve got the four sides. If you construct the midpoints of each of the four sides, and then connect them in a consistent orientation, so clockwise or counterclockwise, then you will get another quadrilateral. You start with the four sides, take the midpoints and connect them. Now you’ve got another quadrilateral. So if you start with a square, you can imagine those mid-points appearing, and you connect them, then that new quadrilateral would be a square. So you have a square inside of a square. This is a picture I think a lot of people can see.
    If you started with a rectangle and you constructed those midpoints, if the rectangle were a non-square rectangle, so longer than it was wide, you can think about it for a moment and maybe draw it, and you’d see a rhombus. Sort of a long, skinny rhombus, depending on the nature of the rectangle. Varignon’s theorem says that regardless of whatever quadrilateral you start with, the quadrilateral you form from those midpoints will be a parallelogram. And I just think that this is so cool.
    KK: It’s always a parallelogram.
    EL: Yeah, that’s really surprising. By every quadrilateral, do you mean only convex ones, is this for all quadrilaterals?
    PH: That’s part of the reason why it’s so much fun to play around with this theorem. It’s true for every quadrilateral, and in fact in some ways, it’s true even for things that aren’t quadrilaterals. In some ways it’s this continual intuition-breaking process with kids when you’re playing around with them. The way you can engage a class with this is you can just tell every student to draw their own quadrilateral and then perform this procedure where they construct the midpoints and connect them. Then you can tell them, ‘Look around. What do you see?’ The first thing the kids see is that everybody drew a square and everybody has a square inscribed, right?
    So this is a nice opportunity to confront kids about their mathematical prejudices. Like if you ask them to draw a quadrilateral, they draw a square. If you ask them to draw a triangle, they draw an equilateral triangle. But then there will always be a couple of kids who drew something a little bit more interesting. You can get kids thinking about what all of those things have in common and start looking for a conjecture. You can kind of push the and prod them to maybe do some different things. So maybe on the next interaction of this activity, we’ll get some rectangles or some arbitrary, some non-special quadrilaterals. Even after a couple rounds of this, you’ll still see that almost all the quadrilaterals drawn are convex. Then you can start pushing the kids to see if they understand that there’s another way to draw a quadrilateral that might pose a problem for Varignon’s theorem. It’s so cool that when you get to that convex one, kids never believe that it’ll still form a parallelogram.
    EL: In the non-convex one.
    PH: That’s right, the concave one, the non-convex. I always get the two words mixed up. Maybe that’s why the kids are so confused. Yeah, the kids will never believe in the non-convex case that it’ll still form a parallelogram. Wow, I can’t believe that.
    KK: It seems like, I looked this up, even if the thing isn’t really a quadrilateral, if you take four points in the plane and draw two triangles that meet where the lines cross, it still works, right?
    PH: Yeah. There’s yet another level to go with this. Now you’ve got the kids like, wait, so for concave, this works? It’s kind of mind-blowing. Then you can start messing around with their idea of what a quadrilateral actually is. If you show them, well, what if I drew a complex quadri-lateral. I don’t use that terminology right away, but just this idea of connecting the vertices in such a way that two sides appear to cross. It can’t possibly work there, can it? The kids don’t know what to think at this point. They think something weird is going around. Amazingly, even if the quadrilateral crosses itself like that, as long as it’s the non-degenerate case, the four points will still make a parallelogram. It’s really remarkable.
    KK: Is there a slick proof of this, or is it one of these crazy things, and you have to construct and construct and construct, and before you know it you’ve lost track of what you’re doing?
    PH: No, that’s another reason why this is such a great high school activity. The proof is really accessible. In fact there are several proofs. But before we talk about my favorite proof of my favorite there, there’s another case, another level you can go with Varignon’s theorem. Often I’ll leave this with students as something to think about, a homework problem or something like that. Varignon’s theorem actually works even if the four points don’t form a quadrilateral, so if the four points aren’t coplanar, say. This process of connecting the midpoints will still form a parallelogram. It’s amazing just that the four points are coplanar. You wouldn’t necessarily expect that the four midpoints would be in the same plane if the four starting points aren’t in the same plane. Moreover, those four points form a parallelogram. It’s such an amazing thing.
    EL: What is your favorite proof, then?
    PH: My favorite proof of Varignon’s theorem is something that connects to a couple of key ideas that we routinely explore in high school geometry. The first is one of the first important theorems about triangles that we prove, that’s simple but has some power. It’s that if you connect the mid-points of two sides of a triangle, that line segment is parallel to the third side. And it’s also half the length. But the parallelism is important.
    The other idea, and I think this is one of the most important ideas that i try to emphasize with students across courses, is the idea of transitivity, of equality or congruence, or in this case par-allelism. The nice proof of Varignon’s theorem is that you imagine all the quadrilaterals and midpoints. And you draw one diagonal. You just think about one diagonal. Now if you cover up half of the quadrilateral, you’ve got a triangle. The line segment connecting those two midpoints is parallel to that diagonal because that’s just that triangle theorem. Now if you cover up the other half of the quadrilateral, you have a second triangle. And that segment is parallel to the diagonal. So both of those line segments are parallel to that diagonal, and therefore by transitivity, they’re parallel to each other, and now you have that the two opposite sides are parallel. And the exact same argument works for the other sides using the other diagonal.
    KK: I like that. My first instinct would be to do some sort of vector analysis. You realize all the sides as vectors and then try to add them up and show that they’re parallel or something.
    PH: Yeah, and in some of the courses i teach, I do some work with vectors, and this is definitely something we do. We explore that proof using vectors, or coordinate geometry. Maybe later in the year we’ll do some work with coordinate geometry. We can prove it that way too.
    EL: Yeah, I think I would immediately go to coordinates. Of course, I would have assumed they were coplanar in the first place. If you tell me it’s a quadrilateral, yeah, it’s going to be there in the plane and not in 3-space.
    PH: I love coordinate geometry, and I definitely have that instinct to run to coordinates when I want to prove something. One of those things you have to be careful of in the high school class is making sure they understand all the assumptions that underly the use of coordinates, and un-derstanding the nature of an arbitrary figure. Going back to one of the first things I said, if you ask kids to draw a quadrilateral, they’re going to draw a square, or if you ask them to draw an arbitrary quadrilateral, they’re often going to draw a square or rectangle. If you ask them to draw an arbitrary quadrilateral in the plane, they might make assumptions about where those coordi-nates are likely to be.
    EL: Yeah.
    KK: Your students are lucky to have you.
    PH: That’s what I tell them!
    KK: Really, to give this much thought to something like this and show all these different per-spectives and how you might come at it in all these different ways, my high school geometry class, I mean I had a fine teacher, but we never saw anything with this kind of sophistication at all.
    PH: It’s fun. I would like to present it as if I sat around and thought deeply about it and had this really thoughtful approach to it, but it just kind of happened. I think, again, that’s why this is one of my favorite theorems. You can just put this in front of students and have them play and just run with this. It’ll just go in so many different directions.
    EL: So what have you chosen to pair with this theorem? What do you enjoy experiencing along with the glory of this theorem?
    PH: This was a tricky one. I feel like when I think of Varignon’s theorem, really focusing on the name, it really transports me to France. I feel like it’s a hearty stew, like boeuf Varignon or something like that. I think you need some crusty bread and a glass of red wine with Varignon’s theorem]. Not my students.
    EL: Crusty bread and grape juice for them. Yeah, I just got back from living in France for six months, and actually I didn’t have any boeuf bourgignon, or Varignon, while I was there, but I did enjoy quite a few things with crusty bread and a glass of red wine. I highly recommend it.
    KK: This has been great fun.
    PH: Yeah, I’ve enjoyed this. You seem to enjoy talking about this more than my students, so this was great for me.
    KK: It helps to be talking to a couple of mathematicians, yeah.
    EL: So, we like to let guests plug websites or anything. So would you like to tell people about your blog or any things you’re involved in that you’d like to share?
    PH: Yeah, sure. I blog, less frequently now than I used to, but still pretty regularly. I blog at mrhonner.com. You can generally find out about what I’m doing at my personal website, pat-rickhonner.com. I’m pretty active on Twitter, @mrhonner.
    KK: Lots of good stuff on Patrick’s blog, especially after the Regents exams. You have a lot to say.
    PH: Not everybody thinks it’s good stuff. I’m glad some people do.
    KK: I don’t live in New York. It’s fine with me.
    EL: Yeah, he has a series kind of taking apart some of the worst questions on the New York Regents exams for math. It can be a little frustrating.
    PH: We just wrapped up Regents season here. Let’s just say there are some posts in the works about what we’re facing. You know, I enjoy it. It always sparks interesting mathematical conver-sations. My goal is just to raise awareness about the toll of these tests and how sometimes it seems like not enough attention is given to making sure these tests are of high quality and are valid.
    KK: I don’t think it’s just a problem in New York, either.
    PH: It is not just a problem in New York.
    KK: Well thanks for joining us, Patrick. This was really great. I learned something today.
    EL: Yeah, me too.
    PH: It was my pleasure. Thanks for having me. Thanks for giving me an opportunity to think about my favorite theorem and come on and talk about it. And maybe Varignon’s theorem will appear in a couple more geometry classes next year because of it.
    KK: Let’s hope.
    EL: Yeah, I hope so.
    KK: Take care.
    PH: Thanks. Bye.

    Show notes (click here)


    Episode 12 - Candice Price Feb 08, 2018
    Show notes Episode 12 - Candice Price Kevin Knudson & Evelyn Lamb Download

    Kevin Knudson: Welcome to My Favorite Theorem. I am Kevin Knudson, professor of mathematics at the University of Florida, and I am joined by my cohost.
    Evelyn Lamb: Hi. I’m Evelyn Lamb. I’m a math and science writer in Salt Lake City, Utah.
    KK: How’s it going?
    EL: Yeah, it’s going okay. It’s a bit smoky here from the fires in the rest of the west. A few in Utah, but I think we’re getting a lot from Montana and Oregon and Washington, too. You can’t see the mountains, which is a little sad. One of the nice things about living here.
    KK: Yeah. Well, Hurricane Irma is bearing down on Florida. I haven’t been to the grocery store yet, but apparently we’re out of water in town. So I might have waited a couple days too late.
    EL: Fill up those bathtubs, I guess.
    KK: I guess. I don’t know. I’m dubious. You know, I lived in Mississippi when Katrina happened, and the eye came right over where we lived, and we never even lost Direct TV. I’m trying not to be cavalier, but we’ll see. Fingers crossed. It’s going to be bad news in south Florida, for sure. I really hope everybody’s OK.
    EL: Yeah, definitely.
    KK: Anyway.
    EL: Fire, brimstone, and water recently.
    KK: Anyway, we’re not here to talk about that. We’re here to talk about math. Today we’re thrilled to have Candice Price with us. Candice, want to say hi?
    Candice Price: Hi everyone!
    KK: Tell us a little bit about yourself.
    CP: Sure. I’m currently an assistant professor of mathematics at the University of San Diego. I got my Ph.D. at the University of Iowa, and I study DNA topology, so knot theory applied to DNA, applied to biology.
    EL: So that’s knot with a ‘k.’
    CP: Yeah, knot.
    KK: San Diego is a big switch from Iowa.
    CP: Yeah, it is. In fact, I had a stopover in New York and a stopover in Texas before getting here. All over.
    EL: You’ve really experienced a lot of different climates and types of people and places.
    CP: Yeah. American culture, really.
    KK: All right. You’ve told us. Evelyn and I know what your favorite theorem is, and I actually had to look this up, and I’m intrigued. So, Candice, what’s your favorite theorem?
    CP: Sure. My favorite theorem is actually John H. Conway’s basic theorem on rational tangles. It’s a really cool theorem. What Conway states, or shows, is that there’s a one-to-one correspondence between the extended rational numbers, so rational numbers and infinity, and what are known as rational tangles. What a rational tangle basically is, is you can take a 3-ball, or a ball, an open ball, and if you put strings inside the ball and attach the strings to the boundary of the ball, so they’re loose in there but fixed, and you add these twists to the strings inside, if you take a count to how many twists you’ve added in these different directions, maybe the direction of west and the direction of south, and if you just write down how many twists you’ve done, first going west and then going south, and then going west, going south, all of those, all the different combinations you can do, you can actually calculate a rational number, and that rational number is attributed to that tangle, to that picture, that three-dimensional object.
    It’s pretty cool because as you can guess, these tangles can get very complicated, but if I gave you a rational number, you could draw that tangle. And you can say that any tangle that has that same rational number, I should be able to just maneuver the strings inside the ball to look like the other tangles. So it’s actually pretty cool to say that something so complicated can just be denoted by fractions.
    EL: Yeah. So how did you encounter this theorem? I encountered it from John Conway at this IAS program for women in math one year, and I don’t think that’s where we met. I don’t remember if you were there.
    CP: I don’t think so.
    EL: Yeah, I remember he did this demonstration. And of course he’s a very engaging, funny speaker. So yeah, how did you encounter it?
    CP: It’s pretty cool, so he has this great video, the rational tangle dance. So it’s fun to show that. I started my graduate work as a master’s student at San Francisco State University, and I had learned a little bit about knot theory (with a ‘k’) as an undergrad. And so when I started my master’s I was introduced to Mariel Vazquez, who studies DNA topology. So she actually uses rational tangles in her research. That was the first time I had even heard that you could do math and biology together, which is a fascinating idea. She had introduced to me the idea of a rational tangle and showed me the theorem, and I read up on the proof, and it’s fascinating and amazing that those two are connected in that way, so that was the first time I saw it.
    KK: Since I hadn’t heard of this theorem before, I looked it up, and I found this really cool classroom activity to do with elementary school kids. You take four kids, and you hand them two ropes. You allow them to do twists, the students on one end of the ropes interchange, and there’s a rotation function.
    CP: Yeah.
    KK: And then when you’re done you get a rational number, and it leads students through these explorations of, well, what does a twist do to an integer? It adds one. The rotate is a -1/x kind of thing.
    CP: Right.
    KK: So I was immediately intrigued. This really would be fun. Not just for middle school kids, maybe my calculus students would like it. Maybe I could find a way to make it relevant to my undergrads. I thought, what great fun.
    CP: Yeah. I think it’s even a cool way to show students that with just a basic mathematical entity, fractions or rational numbers, you can perform higher mathematics. It’s pretty cool.
    KK: This sort of begs the question: are there non-rational tangles? There must be.
    CP: Yes there are! It categorizes these rational tangles, but there is not yet a categorization for non-rational tangles. There are two types. One is called prime, and one is called locally knotted. So the idea of locally knotted is that one of the strands just has a knot on it. A knot is exactly what you think about where you have a knot in your shoestring. Then prime, which is great, is all of the tangles that are not rational and not locally knotted. So it’s this space where we’ve dumped the rest of the tangles.
    KK: That’s sort of unfortunate.
    CP: Yeah, especially the choice of words.
    KK: You would think that the primes would be a subset, somehow, of the rational tangles.
    CP: You would hope.
    EL: So how do these rational tangles show up in DNA topology?
    CP: That’s a great question. So your DNA, you can think of as long, thin strings. That’s how I think about it. And it can wrap around itself, and in fact your DNA is naturally coiled around itself. That’s where that twisting action comes, so you have these two strings, and each string, we know, is a double helix. But I don’t care about the helical twist. I just care about how the DNA wraps around itself. These two strings can wind around, just based on packing issues, or a protein can come about and add these twists to it, and naturally how it just twists around. Visually, it looks like what is happening with rational tangles. Visually, the example that Kevin was mentioning, that we have the students with the two ropes, and they’re sort of twisting the ropes around, that’s what your DNA is doing. It turns into a great model, visually and topologically, of your DNA.
    KK: Very cool.
    CP: I like it.
    KK: Wait, where does infinity come from, which one is that? It’s the inverse of 0 somehow, so you rotate the 0 strand?
    CP: Yes, perfect. Very good.
    KK: So you change your point of view, like when I’m proving the mean value theorem in calculus, I just say, well, it’s Rolle’s theorem as Forrest Gump would look at it, how he tilts his head.
    CP: Right. I’m teaching calculus. I might have to use that. That’s good. I mean, hopefully they’ll know who Forrest Gump is.
    KK: Well, right. You’re sort of dating yourself.
    CP: That’s also a fun conversation to have with them.
    KK: Sure. So another fun conversation on this podcast is the pairing. We ask our guests to pair their theorem with something. What have you chosen to pair Conway’s theorem with?
    CP: So I thought a lot about this. So being in California, right, what I paired this with is a Neapolitan shake from In n Out burger. And the reason for that is, you’ve sort of taken these three different flavors, equally delicious on their own, right, rational numbers, topology, and DNA, and you put them together in this really beautiful, delicious shake. So the Neapolitan shake from In n Out burger is probably my favorite dessert, so for me, it’s a good pairing with Conway’s rational tangle theorem.
    KK: I’ve only eaten at In n Out once in my life, sadly, and I didn’t have that shake, but I’m trying to picture this. So they must not mix it up too hard.
    CP: They don’t, not too hard. So there’s a possibility of just getting strawberry, just getting vanilla, just getting chocolate, but then you can at some point get all three flavors together, and it’s pretty amazing.
    KK: So I can imagine if you mix it too much, it would just be, like, tan. It would just be this weird color.
    CP: Maybe not as delicious looking as it is tasting.
    KK: That’s an interesting idea.
    CP: It’s pretty cool.
    KK: So we also like to give our guests a chance to plug anything they’re working on. Talk about your blog, or anything going on.
    CP: Sure. I am always doing a lot of things. I am hoping I can take this time to plug, in February we have a website—we is myself, Shelby Wilson, Raegan Higgins, and Erica Graham—a website called Mathematically Gifted and Black where we showcase or spotlight every day a contemporary black mathematician and their contributions to mathematics, and we’re working on that now. We’ll have an article in the AMS Notices in February coming up. It’s up now so you can see it. We launched in February 2017. It’s a great website. We’re really proud of it.
    EL: Yeah. Last year it was a lot of fun to see who was going to be coming on the little calendar each time and read a little bit about their work. You guys did a really nice job with that.
    CP: Thanks. We’re very proud, and I think the AMS will put a couple of posters around the website as well.
    KK: Great. Well, Candice, thanks for joining us.
    CP: Thank you.
    KK: This has been good fun. I like learning new theorems. Thanks again.
    CP: Yeah, of course. Thank you. I enjoyed it.
    [outro]

    Show notes (click here)


    Episode 11 - Jeanne Nielsen Clelland Jan 25, 2018
    Show notes Episode 11 - Jeanne Nielsen Clelland Kevin Knudson & Evelyn Lamb Download

    Kevin Knudson: Welcome to My Favorite Theorem. I’m Kevin Knudson, professor of mathematics at the University of Florida. I’m flying solo in this episode. I’m at the Geometry in Gerrymandering workshop at Tufts University, sponsored by the Metric Geometry, what is it called, Metric Geometry and Gerrymandering Group, MGGG. It’s been a fantastic week. I’m without my cohost Evelyn Lamb in this episode because I’m on location, and I’m currently sitting in the lobby of my bed and breakfast with my very old friend, not old as in age, just going way back, friend, Jeanne Nielsen Clelland.
    Jeanne Clelland: Hi Kevin. Thanks for having me.
    KK: So you’re at the University of Colorado, yes?
    JC: University of Colorado at Boulder, yes.
    KK: Tell everyone about yourself.
    JC: Well, as you said, we’re old friends, going all the way back to grad school.
    KK: Indeed. Let’s not say how long.
    JC: Let’s not say how long. That’s a good idea. We went to graduate school together. My area is differential geometry and applications of geometry to differential equations. I’m a professor at the University of Colorado at Boulder, and I’m also really enjoying this gerrymandering conference, and I’m really happy to be here.
    KK: Let’s see if we can solve that problem. Although, as we learned today, it appears to be NP-hard.
    JC: Right.
    KK: That shouldn’t be surprising in some sense. Anyway, hey, let’s put math to work for democracy. Whether we can solve the problem or not, maybe we can make it better. So I know your favorite theorem, but why don’t you tell our listeners. What’s your favorite theorem?
    JC: My favorite theorem is the Gauss-Bonnet theorem.
    KK: That’s awesome because if anybody’s gone to our Facebook page, My Favorite Theorem, or our Twitter feed, @myfavethm, the banner picture, the theorem stated there is the Gauss-Bonnet theorem. That’s accidental. I just thought the statement looked pretty.
    JC: Yeah, and when I first looked at your page, I saw that. And I thought, well, I guess my favorite theorem is already taken since it’s your banner page, so I was really excited to hear that I could talk about it.
    KK: No, no, no. In fact, I was doing one last week, and the person mentioned they might do Gauss-Bonnet, and I said no, no, no. I have an expert on Gauss-Bonnet who’s going to do it for us. So why don’t you tell us what Gauss-Bonnet is?
    JC: OK. So Gauss-Bonnet is about a relationship between, so it’s in differential geometry. It comes from the geometry of surfaces, and you can start with surfaces in 3-dimensional space that are easy to visualize. And there are several notions of curvature for surfaces. One of these notions is called the Gauss curvature, and roughly it measures whether a surface is bowl-shaped or saddle-shaped. So if the Gauss curvature is positive, then you think the surface looks more like a bowl, like a sphere is the prototypical example of positive Gauss curvature. If the Gauss curvature is negative, then your surface is shaped more like a saddle, and if the Gauss curvature is zero, then you think your surface, well the prototypical example is a plane, a surface that’s flat, but in fact this is a notion that is metrically invariant, which means if you take a surface and bend it without stretching it, you won’t change the Gauss curvature.
    KK: OK.
    JC: So for instance I could take a flat piece of paper and wrap it up into a cylinder.
    KK: Yes.
    JC: And since that doesn’t change how I measure distance, at least small distances on that piece of paper, a cylinder also has Gauss curvature zero.
    KK: So this is a global condition?
    JC: No, it’s local.
    KK: Right.
    JC: It’s a function on the surface, so at every point you can talk about the Gauss curvature at a point. So of course the examples I’ve given you, the sphere, the plane, those are surfaces where the Gauss curvature is constant, but on most surfaces this is a function, it varies from point to point.
    KK: Right, so a donut, a torus, on the inside it would be negative, right?
    JC: Right.
    KK: But on the outside,
    JC: That’s exactly right, and that’s a great example. We’re going to come back to the example of the torus.
    KK: Good.
    JC: So at the other extreme for surface, particularly for compact surfaces, you have topology, which is your area. And there’s a fundamental invariant of surfaces called the Euler characteristic. And the way you can compute this is really fun. You draw a graph, and the mathematical notion of a graph is basically you have points, which are called vertices, you have edges joining your vertices, and then you have regions enclosed by these edges, which are called faces.
    KK: Yes.
    JC: And if you take a surface, you can draw a graph on it any way you like. You count the number of vertices V, the number of edges E, and the number of faces F. You compute the number V-E+F, and no matter how you drew your graph, that number will be the same for any graph on a given surface.
    KK: Which is remarkable enough.
    JC: That is remarkable enough, right, that’s hugely remarkable. That’s a very famous theorem that makes this number a topological invariant, so for instance the Euler characteristic is 2, the Euler characteristic of a donut is zero. If you were to take, say, a donut with multiple holes, my son really loves these things called two-tone knots, which are donuts. A two-tone has Euler characteristic of -2, and generally the more holes you add, the more negative the Euler characteristic.
    KK: Right, so the formula is 2 minus two times the number of holes, or 2-2g.
    JC: Yes, and that’s for a compact surface.
    KK: Compact surfaces.
    JC: And it gets more complicated for non-compact. So the Gauss-Bonnet theorem in its simplest form, and let me just state it for compact surfaces, so I’m not worried about boundary, it says if you take the Gauss curvature, which is this function, and you integrate that function over the surface, the number that you get is 2π times the Euler characteristic.
    KK: This blew my mind the first time I saw it.
    JC: This is an incredible relationship, a very surprising relationship between geometry and topology. So for instance, if you take your surface and you wiggle it, you bend it, you can change that Gauss curvature a lot.
    KK: Sure.
    JC: You can introduce all sorts of wiggles in it from point to point. What this theorem says is that however you do that, all those wiggles have to cancel out because the integral of that function does not change if you wiggle the surface. It’s this absolutely incredible fact.
    KK: So for example take a sphere. So we would get 4π.
    JC: 4π.
    KK: A sphere has constant sectional curvature 1. I guess, can you change that? You can, right?
    JC: Sure!
    KK: But if you maybe stretch it into an ellipsoid, the curvature is still maybe going to be positive, it’s going to be really steep at the pointy ends but flatter in the middle. So the way I always visualized this was that yeah, you might bend and stretch, which topologists don’t care about, and this integral—and the way we think about integrals is that they’re just big sums, right?—so you increase some of the numbers and decrease some of the numbers, so they’re just canceling out.
    JC: Not only that, these numbers are scale invariant. So if you take a big sphere versus a small sphere, the big sphere has more area, but the absolute value of the curvature function is smaller, and those things cancel out. So the integral remains 4π.
    KK: Right, so the surface of the Earth, for example, we can’t really see the curvature.
    JC: Right.
    KK: But it is curved.
    JC: It is curved, and the area is so big that the integral of that very small function over that very large area would still be 4π.
    KK: Right. So on the donut, right, we’re getting this cancelation. On the inside it’s negative, and it’s going to be 0 in some points, and on the outside it’s positive.
    JC: Right. That’s really the amazing thing about the donut. It’s this unique surface where you get zero. So you have this outer part of the donut where the Gauss curvature is positive, the inner part where it’s negative, and no matter what you do to your donut, how irregularly shaped you make it, just the fact that it’s donut shaped means that those regions of positive and negative curvature exactly cancel each other out.
    KK: Wow. Yeah, it’s a remarkable theorem. Great connection between geometry and topology. Do you want to talk about the noncompact case?
    JC: This also gets interesting for surfaces with boundary. It actually starts, when I teach this in a differential geometry class, where this starts is a very classical idea called the angle excess theorem. And this goes back to Euclidean geometry. So everybody knows in flat Euclidean geometry, if you draw a triangle, what’s the sum of the angles inside the triangle?
    KK: Yeah, 180 degrees.
    JC: 180 degrees, π, depending on whether you want to work in degrees or radians. This is a consequence of the parallel postulate, and in the history of developing non-Euclidean geometry, what happened is people had developed alternate ideas of geometry with alternate versions of the parallel postulate. So in spherical geometry, imagine you draw a triangle on the sphere. Say you’ve got a globe. Take a triangle with points: one vertex is at the north pole, and two vertices are at the Equator. Say you’ve moved a quarter of the way around the circle, and the straight lines in this geometry are great circles.
    KK: Yes.
    JC: So draw a triangle between those three points with great circles. That’s a triangle with three right angles.
    KK: 270 degrees.
    JC: Right, 270 degrees. What the angle excess theorem says is that the difference, and we use radians, so that has 3π/2 angle, instead of π. So it says that the difference of those two numbers is the integral of the Gauss curvature over that triangle.
    KK: Oh wow, OK. OK, I believe that.
    JC: As we were saying for a sphere, the total Gauss curvature integral is 4π. This triangle I’ve just described takes up an eighth of the sphere, it’s an octant. So its area is π/2, so that’s the difference of its Gauss curvature. So that’s why the difference of sum of those angles and π is π/2. So that’s where this theorem starts, and ultimately the way you prove the angle excess theorem, basically it boils down to Green’s theorem, which I was very excited to hear Amie Wilkinson talk about in one of your previous episodes. It’s really just Green’s theorem to prove the angle excess theorem. So from there, the way you prove the global Gauss-Bonnet theorem is you triangulate your surface. You cut it up into geodesic triangles, you apply the angle excess theorem to each of those triangles, you add them all up, and you count very carefully based on the graph you have drawn of triangles how many vertices, how many edges, and how many faces. And when you count carefully, the Euler characteristic pops out on the other side.
    KK: Right, OK.
    JC: It’s this very neat combination of classical things, the angle excess theorem and combinatorics. It’s fun teaching an undergraduate course when you tell them counting is hard.
    KK: It is hard.
    JC: And they don’t believe you until you show them the ways it’s hard.
    KK: There’s no way. I can’t count.
    JC: So it’s a really fun theorem to do with students. It’s the culmination of the differential geometry class that I teach for undergraduates. I spend the whole semester saying, “Just wait until we get to Gauss-Bonnet! You’re going to think this is really cool!” And when we get there, it really does live up to the hype. They’re really excited by it.
    KK: Yeah. So this leads to the question. We like to pair our theorems with something. What have you chosen to pair the Gauss-Bonnet theorem with?
    JC: Well the obvious thing would be donuts.
    KK: Sure.
    JC: And in fact I do sometimes bring in donuts to class to celebrate the end of the class, but you know, this is such a culminating theorem, I really wanted to pair it with something celebratory, like a fireworks display or some sort of very celebratory piece of music.
    KK: I can get on with that. It’s true, donuts seem awfully pedestrian.
    JC: They do. Donuts are great because of the content of the theorem. They’re a little too pedestrian.
    KK: So a fireworks display with what, 1812 Overture?
    JC: Something like that.
    KK: Really, this is the end. Bang!
    JC: I think it deserves the 1812 Overture.
    KK: That’s a really good one, OK. And maybe we’ll try to get that into the podcast.
    JC: That would be great.
    KK: A nice public domain thing if I can find it.
    [1812 Overture plays]
    JC: Sounds great.
    KK: So we like to give our guests a chance to plug something. So you published a book recently?
    JC: I did. I recently published a book. It’s called From Frenet to Cartan: The Method of Moving Frames. It’s published in the American Math Society’s graduate series, and it’s basically designed to be a second course in differential geometry, so for advanced undergraduates or beginning graduate students who have had a course in curves and surfaces. Hopefully it’s accessible at that level, and it was really fun. It largely grew out of working with students doing independent study, so I really wrote this book in a way that’s intended to be very student-friendly. It’s informal in style and written the way I would talk to a student in my office. I’m very happy with how it came out, so if this is a topic that’s interesting to any of your listeners, check it out.
    KK: That’s great. I took curves and surfaces from your advisor, Robert Bryant, who’s the nicest guy you’ve ever met.
    JC: Oh, he’s wonderful.
    KK: Everybody loves Robert. That was the last differential geometry course I took, so maybe I should read your book.
    JC: Let me give him credit, too. Where this originally came from, when I was a new Ph.D., well relatively new, three years post-Ph.D., Robert invited me to give a series of graduate lectures with him at MSRI, and this book grew out of notes I wrote for that workshop many, many years ago. And Robert, when I very naively said to him, “You know, I have all these lecture notes I should turn into a book,” Robert, having written a book, should have laughed at me, but instead he said, “Yeah, you should!” And it became a back burner project for a long time.
    KK: More than a decade, probably.
    JC: Yeah, but eventually, I’ve had so much fun working with students on this project.
    KK: I’ve written two books, and it’s really, it’s so much work.
    JC: You don’t do it for the money.
    KK: You really don’t do it for the money, that’s for sure. And of course it’s great you had such a model in Robert, as a teacher and an expositor.
    JC: I count myself extremely fortunate to have had him as my advisor.
    KK: Well, Jeanne, this has been fun. Thanks for joining us.
    JC: Thanks for having me.
    [outro]

    Show notes (click here)


    Episode 10 - Mohamed Omar Jan 11, 2018
    Show notes Episode 10 - Mohamed Omar Kevin Knudson & Evelyn Lamb Download

    Kevin Knudson: Welcome to My Favorite Theorem. I’m your host Kevin Knudson, professor of mathematics at the University of Florida. And I’m joined by my cohost.
    EL: I’m Evelyn Lamb, a freelance math and science writer in Salt Lake City, Utah.
    KK: Welcome home.
    EL: Yeah, thanks. I just got back from Paris a week ago, and I’m almost back on Utah time. So right now I’m waking up very early, but not 3 in the morning, more like 5 or 6.
    KK: Wait until you’re my age, and then you’ll just wake up early in the morning because you’re my age.
    EL: Yeah. I was talking to my grandma the other day, and I was saying I was waking up early, and she said, Oh, I woke up at 4 this morning.
    KK: Yeah, that’s when I woke up. It’s not cool. I don’t think I’m as old as your grandmother.
    EL: I doubt it.
    KK: But I’m just here to tell you, winter is coming, let me put it that way. We’re pleased today to welcome Mohamed Omar. Mohamed, why don’t you tell everyone a little bit.
    MO: Great to be on the podcast. My name is Dr. Mohamed Omar. I’m a professor at Harvey Mudd College. My area of specialty is algebra and combinatorics, and I like pure and applied flavors of that, so theoretical work and also seeing it come to light in a lot of different sciences and computer science. I especially like working with students, so they’re really involved in the work that I do. And I just generally like to be playful with math, you know, have a fun time, and things like this podcast.
    KK: Cool, that’s what we aim for.
    EL: And I guess combinatorics probably lends itself to a lot of fun games to play, or it always seems like it.
    MO: Yeah. The thing I really like about it is that you can see it come to life in a lot of games, and a lot of hobbies can motivate the work that comes up in it. But at the same time, you can see it as a lens for learning a lot of more advanced math, such as, like, abstract algebra, sort of as a gateway to subjects like that. So I love this diversity in that respect.
    KK: I always thought combinatorics was hard. I thought I knew how to count until I tried to learn combinatorics. It’s like, wait a minute, I can’t count anything.
    MO: It’s difficult when you have to deal with distinguishability and indistinguishability and mixing them, and you sort of get them confused. Yeah, definitely.
    KK: Yeah, what’s it like to work at Harvey Mudd? That always seemed like a really interesting place to be.
    MO: Harvey Mudd is great. I think the aspects I like of it a lot are that the students are just intrinsically interested and motivated in math and science, and they’re really excited about it. And so it really feels like you’re at a place where people are having a lot of fun with a lot of the tools they learn. So when you’re teaching there, it’s a really interactive, fun experience with the students. There’s a lot of active learning that goes on because the students are so interested in these things. It’s a lot of fun.
    KK: Very cool. So, Mohamed, what’s your favorite theorem?
    MO: First of all, my favorite theorem is a lemma. Actually a theorem, but usually referred to as a lemma.
    KK: Lemmas are where all the work is, right?
    MO: Exactly. It’s funny you mention combinatorics because this is actually in combinatorics. It’s called Burnside's Lemma. Yeah, so I love Burnside's Lemma a lot, so maybe I’ll give a little idea of what it is and give an idea in light of what you mentioned, which is that combinatorics can be quite hard. So I’ll start with a problem that’s hard, a combinatorial one that’s hard. So imagine you have a cube. A cube has six faces, right? And say you ask the naive question how many ways are there to paint the faces of the cube with colors red, green, and blue.
    KK: Right.
    MO: You think, there are six faces, and the top face is either red, or green, or blue, and for every choice of color I use there, another face is red or green or blue, etc. So the number of colorings should be 3x3x3x3x3x3, 3^6.
    EL: Right.
    MO: But then, you know, you can put a little bit of a twist on this. You can say, how many ways are there to do this if you consider two colorings to be the same if you take the cube and rotate it, take one coloring, rotate the cube, and get another coloring.
    EL: Right. If you had the red face on the left side, it could be on the top, and that would be the same.
    MO: One naive approach that people tend to think works when they first are faced with this, is they think, OK, there are 6 faces, so maybe I can permute things 6 ways, so I divide the total number by 6.
    KK: Wrong.
    MO: Exactly. There are a lot of reasons. One is sort of the empirical reason. You said the answer was 3^6 if we’re not caring about symmetry. If you divide that by 6, there’s a little bit of a problem, right?
    EL: Yeah.
    MO: You can kind of see. If you have a painting where all the faces are red, no matter how you rotate that, you’re going to end up with the same coloring. But as you mentioned, if you color one face red and the rest green, for instance, then you get six different colorings when you rotate this cube around. So you’ve got to do something a little bit different. And Burnside's lemma essentially gives you a nice quick way to approach this by looking at something that’s completely different but easy to calculate. And so this is sort of why I love it a lot. It’s a really, really cool theorem that you can sort of explain at a maybe discrete math kind of level if you’re teaching at a university.
    KK: So the actual statement, let’s see if I can remember this. It’s something like the number of colorings would be something like 1 over the order of the group of rotations times the sum of what is it the number of elements in each orbit, or something like that? I used to know this pretty well, and I’ve forgotten it now.
    MO: Yeah, so something like that. So a way to think about it is, you have your object, and it has a bunch of symmetries. So if you took a square and you were coloring, say, the edges, this is an analogous situation to the faces of the cube. A square has 8 symmetries. There are the four rotations, but then you can also flip along axes that go through opposite edges, and then axes that go through opposite vertices.
    So what Burnside's lemma says is something like this. If you want to know the number of ways to color, up to this rotational symmetry, you can look at every single one of these symmetries that you have. In the square it’s 8, in the cube it turns out to be 24. And for every single symmetry, you ask yourself how many ways are there to color with the three colors you have where the coloring does not change under that symmetry.
    KK: The number of things fixed, essentially, right.
    MO: Exactly. The number of things fixed by the symmetries. So like I mentioned, the cube has 24 symmetries. So let’s take an example of one. Let’s say you put a rod through the center of two opposite faces of the cube.
    KK: Right.
    MO: And you rotate 90 degrees along that. So you’re thinking about the top face and the bottom face and just rotating 90 degrees. Let’s just think about the colorings that would remain unchanged by that symmetry. So you’re free to choose whatever you’d like for the top and bottom face. But all the side faces will have to have the same color. Because as soon as you get another face. Whatever was in that face is now rotated 90 degrees as well. So if you count the number of colorings fixed by that rotation about the rod through the opposite faces, you get something like, well you have three choices for those side faces. As soon as you choose the color for one, you’re forced to use the same color for the rest. And then you have freedom in your top and bottom faces. So that’s just one of the symmetries. Now if you did that for every single symmetry and took the average of them, it turns out to be the number of ways to color the faces of the cube up to rotational symmetry in general.
    So it’s kind of weird. There’s sort of two things that are going on. One is why in the world would looking at the symmetries and counting the number of colorings fixed under the symmetry have anything to do with the number of colorings in total up to symmetry in general? It’s not clear what the relationship there is at first. But the real cool part is that if you take every single symmetry and count the number of colorings, that’s a systematic thing you can do without having to think too hard. It’s a nice formula you can get at the answer quite quickly even though it seems like a complicated thing that you’re doing.
    EL: Yeah. So I guess that naive way we were talking about to approach this where you just say, well I have three choices for this one, three choices for that one, you almost kind of look at it from the opposite side. Instead of thinking about how I’m painting things, I think about how I’m turning things. And then looking at it on a case by case basis rather than looking at the individual faces, maybe.
    MO: Exactly. When I first saw this, I saw this as an undergrad, and I was like, “What?!” That was my initial reaction. It was a cool way to make some of this abstract math we were learning really come to life. And I could see what was happening in the mathematics physically, and that gave me a lot of intuition for a lot of the later things we were learning related to that theorem.
    EL: Was that in a combinatorics class, or discrete math class?
    MO: It was actually in a standalone combinatorics class that I learned this. And now another reason I really like this lemma is that I teach it in a discrete math course that I teach at Harvey Mudd, but then I revisit it in an abstract algebra course because really, you can prove this theorem using a theorem in abstract algebra called the orbit stabilizer theorem. So orbits are all of these different, you take one coloring, spin it around in all possible ways, you get a whole bunch of different ones, and stabilizers you can think of as taking one symmetry and asking what colorings are fixed under that symmetry. So that’s in our example what those two things are. In abstract algebra, there’s this orbit stabilizer theorem that has to do with more general objects: groups, like you mentioned. And then one of the things I really like about this theorem is that it sets the stage for even more advanced math like representation theory. I feel like a lot of the introductory concepts in a representation theory course really come back to things you play with in Burnside’s Lemma. It’s really cool in its versatility like that.
    KK: That’s the context I know it in. So I haven’t taught group theory in 10 years or so, but it was in that course. Now I’m remembering all of this. It’s coming back. This is good. I’m glad we’re having this conversation. I’m with you. I think this is a really remarkable theorem. But I never took a combinatorics course that was deep enough where we got this far. I only know it from the groups acting on sets point of view, which is how you prove this thing, right? And as you say, it’s definitely leads into representation theory because, as you say, you can build representations of your groups. You just take a basis for a vector space and let it act this way, and a lot of those character formulas really drop out of this.
    MO: Exactly.
    KK: Very cool.
    EL: So it sounds like you did not have a hard time choosing your favorite theorem. This was really, you sound very excited about this theorem.
    MO: The way I tried to think about what my favorite theorem was what theorem to I constantly revisit in multiple different courses? If I do that, I must like it, right? And then I thought, hey, Burnside's Lemma is one that I teach in multiple courses because I like all the different perspectives that you can view it from. Then I had this thought: is Burnside's Lemma really a theorem?
    KK: Yeah, it is.
    MO: I felt justified in for the following reason, which is I think this lemma’s actually due to Frobenius, not Burnside. I thought, since the Burnside part is not really due to Burnside, then maybe the lemma part really is a theorem.
    EL: I must say, Burnside sounds like it should be a Civil War general or something.
    MO: Definitely.
    EL: So what have you chosen to pair with your theorem?
    MO: So I thought a chessboard marble cake would be perfect.
    KK: Absolutely.
    EL: OK!
    MO: So first of all, I had a slice of one just about a few hours ago. It was my brother’s birthday recently, and I’m visiting family. There was leftover cake, and I indulged. But then I thought yeah, one of the prototypical problems when playing around with Burnside's Lemma is how many ways are there to color the cells of a chessboard up to rotational symmetry? So when I was eating the cake, I thought, hey, this is perfect!
    EL: That’s great.
    KK: How big of a chessboard was it?
    MO: 8x8.
    KK: Wow, that’s pretty remarkable.
    MO: It was a big cake. I had a big piece.
    KK: So when you sliced into it, was it 8x8 that way, or 8x8 across the top?
    MO: Across the top.
    KK: I’m sort of imagining, so my sister in law is a pastry chef, and she makes these remarkably interesting looking things, and it’s usually more like a 3x3, the standard if you go vertical.
    EL: I’ve never tried to make a chessboard cake. I like to bake a lot, but anything that involves me being fussy about how something looks is just not for me. In baking. Eating I’m happy with.
    MO: I’m the same. I really enjoy cooking a lot. I enjoy the cooking and the eating, not the design.
    KK: Yeah, I’m right there with you. Well this has been fun. Thanks for joining us, Mohamed.
    EL: Yeah.
    MO: Thank you. This has been really enjoyable.
    KK: Take care.
    MO: Thank you.
    [outro]

    Show notes (click here)


    Episode 9 - Ami Radunskaya Dec 28, 2017
    Show notes Episode 9 - Ami Radunskaya Kevin Knudson & Evelyn Lamb Download

    Evelyn Lamb: Welcome to My Favorite Theorem. I’m your host Evelyn Lamb. I’m a freelance math and science writer based in Salt Lake City. And today I am not joined by my cohost Kevin Knudson. Today I am solo for a very special episode of My Favorite Theorem because I am at MathFest, the annual summer meeting of the Mathematical Association of America. This year it’s in Chicago, a city I love. I lived here for a couple years, and it has been very fun to be back here with the big buildings and the lake and everything. There are about 2,000 other mathematicians here if I understand correctly. It’s a very busy few days with lots of talks to attend and friends to see, and I am very grateful that Ami Radunskaya has taken the time to record this podcast with me. So will you tell me a little bit about yourself?
    Ami Radunskaya: Hi Evelyn. Thanks. I’m happy to be here at MathFest and talking to you. It’s a very fun conference for me. By way of introduction, I’m the current president for the Association for Women in Mathematics, and I’m a math professor at Pomona College in Claremont, which is a small liberal arts college in the Los Angeles County. My Ph.D. was in ergodic theory, something I am going to talk about a little bit. I went to Stanford for my doctorate, and before that I was an undergraduate at Berkeley. So I grew up in Berkeley, and it was very hard to leave.
    EL: Yeah. You fall in love with the Bay Area if you go there.
    AR: It’s a place dear to my heart, but I was actually born in Chicago.
    EL: Oh really?
    AR: So I used to visit my grandparents here, and it brings back memories of the Museum of Science and Industry and all those cool exhibits, so I’m loving being back here.
    EL: Yeah, we lived in Hyde Park when we were here, so yeah, the Museum of Science and Industry.
    AR: I think I was born there, Hyde Park.
    EL: Oh? Good for you.
    AR: My dad was one of the first Ph.D.s in statistics from the University of Chicago.
    EL: Oh, nice.
    AR: Although he later became an economist.
    EL: Cool. So, what is your favorite theorem?
    AR: I’m thinking today my favorite theorem is the Birkhoff ergodic theorem. I like it because it’s a very visual theorem. Can I kind of explain to you what it is?
    EL: Yeah.
    AR: So I’m not sure if you know what ergodic means. I actually first went into the area because I thought it was such a cool word, ergodic.
    EL: Yeah, it is a cool word.
    AR: I found out it comes from the Greek word ergod for path. So I’ve always loved the mathematics that describes change and structures evolving, so before I was a mathematician I was a professional cellist for about 10 years. Music and math are sort of as one in my mind, and that’s why I think I’m particularly attracted to the kinds of mathematics and the kinds of theory that describes how things change, what’s expected, what’s unexpected, what do we see coming out of a process, a dynamical process? So before I state the theorem, I need to tell you what ergodic means.
    EL: Yeah.
    AR: It’s an adjective. We’re talking about a function. We say a function is ergodic if it takes points: imagine you put a value into a function, you get out a new value. You put that value back in to the function, you get a new value. Repeat that over and over and over again, and now the function is ergodic if that set of points sort of visits everywhere in the space. So we say more technically a function is ergodic if the invariant sets, the sets it leaves alone, the sets that get mapped to themselves, are either the whole space or virtually nothing. A function is ergodic, a map is ergodic, if the invariant sets either have, we say, full measure or zero measure. So if you know anything about probability, it’s probability 1 or probability zero. I think that’s an easy way to think about measure.
    EL: Yeah, and I think I’ve heard people describe ergodic as the time average is equal to the space average, so things are distributing very evenly when you look at long time scales. Is that right?
    AR: Well that’s exactly the ergodic theorem. So that’s a theorem!
    EL: Oh no!
    AR: No, so that’s cool that you’ve heard of that. What I just said was that something is ergodic if the sets that it leaves unchanged are either everything or nothing, so these points, we call them the orbits, go everywhere around the set, but that doesn’t tell you how often they visit a particular piece of your space, whereas the ergodic theorem, so there are two versions of it. My favorite one is the one, they call it the pointwise ergodic theorem, because I think it’s easier to visualize. And it’s attributed to Birkhoff. So sometimes it’s called the Birkhoff ergodic theorem. And it’s exactly what you just said. So if you have an ergodic function, and then we start with a point and we sort of average it over many, many applications of the function, or iterations of the function, so that’s the time average. We think of applying this function once every time unit. The time average is the same as the integral of that function over the space. That’s the space average. So you can either take the function and see what it looks like over the entire space. And remember, that gives you, like, sizes of sets as well. So you might have your space, your function might be really big in the middle of the space, so when you integrate it over that piece, you’ll get a big hump. And it says that if I start iterating at any point, it’ll spend a lot more time in the space where the function is big. So the time average is equal to the space average. So that is the pointwise Birkhoff ergodic theorem. And I think it’s really cool because if you think about, say, if you’ve ever seen pictures of fractal attractors or something, so often these dynamical systems, these functions we’re looking at, are ergodic on their attractor. All the points get sucked into a certain subset, and then on that subset they stay on it forever and move around, so they’re ergodic on that attractor.
    EL: Yeah.
    AR: So if we just, say, take a computer and start with a number and plug it in our function and keep iterating, or maybe it’s a two-dimensional vector, or maybe it’s even a little shape, and you start iterating, you see a pattern appear because that point is visiting that set in exactly the right amount. Certain parts are darker, certain parts are lighter, and it’s as if, I don’t know in the old days, before digital cameras, we would actually develop photographs. Imagine you put that blank page in the developing fluid, and you sort of see it gradually appear. And it’s just like that. The ergodic theorem gives us that magical appearance of these shapes of these attractors.
    EL: Yeah. That’s a fun image. I’m almost imagining a Polaroid picture, where it slowly, you know, you see that coming out.
    AR: It’s the same idea. If you want to think about it another way, you’re sort of experiencing this process. You are the point, and you’re going around in your life. If your life is ergodic, and a lot of time it is, it says that you’ll keep bumping into certain things more often than others. What are those things you’ll bump into more often? Well the things that have higher measure for you, have higher meaning.
    EL: Yeah. That’s a beautiful way to think about it. You kind of choose what you’re doing, but you’re guided.
    AR: I call it, one measure I put on my life is the fun factor.
    EL: That’s a good one.
    AR: If your fun factor is higher, you’ll go there more often.
    EL: Yeah. It also says something like, if you know what you value, you can choose to live your life so that you do visit those places more. That’s a good lesson. Let the ergodic theorem guide you in your life. OK, so what have you chosen to pair with this theorem?
    AR: So the theorem has a lot of motion in it. A lot of motion, a lot of visualization. I think as far as music, it’s not so hard to think of an ergodic musical idea. Music is, after all, structures evolving through space.
    EL: Exactly.
    AR: I think I would pair Steve Reich’s Violin Phase. Do you know that piece?
    EL: Yeah, yeah.
    AR: So what it is, it’s a phrase on the violin, then you hear another copy of it playing at the same time. It’s a repetitive phrase, but one of them gets slightly out of phase with the other, and more and more and more and more. And what you hear are how those two combine in different ways as they get more and more and more and more out of phase. And if you think of that visually, you might think of rotating a circle bit by bit by bit, and in fact, we know irrational rotations of the circle are ergodic. You visit everywhere, so you hear all these different combinations of those patterns. So Steve Reich Violin Phase. He has a lot of pattern music. Some of it is less ergodic, I mean, you only hear certain things together. But I think that continuous phase thing is pretty cool.
    EL: Yeah. And I think I’ve heard it as Piano Phase more often than Violin Phase.
    AR: It’s a different piece. He wrote a bazillion of them.
    EL: Yeah, but I guess the same idea. I really like your circle analogy. I almost imagine, maybe the notes are gears sticking out of the circle, and they line up sometimes. Because even when it’s not completely back in phase, sometimes the notes are playing at the same time but at a different part of the phrase. They almost lock in together for a little while, and then turn a little bit more and get out again and then lock in again at a different point in the phrase. Yeah, that’s a really neat visual. Have you performed much Steve Reich music?
    AR: I’ve performed some, mostly his ensemble pieces, which are really fun because you have to focus. One of my favorites of his is called Clapping Music because you can do it with just two people. It’s the same idea as the Violin Phase, but it’s a discrete shift each time, so a shift by an eighth note. So the pattern is [clapping]. One person claps that over and over and over, and the other person claps that same rhythm but shifts it by one eighth note each time. So since that pattern is 12 beats long, you come back to it after 12 beats. So it’s discretized. You do each one twice, so it’s 24, so it’s long enough.
    EL: So that’s a non-ergodic one, a periodic transformation.
    AR: Exactly. So that one I do a lot when I give talks about how we can describe mathematics with its musical manifestations, but we can also describe music mathematically.
    EL: Just like you, music is one of my loves too. I played viola for a long time. I’ve never performed any Steve Reich, and I’m glad you didn’t ask me to spontaneously perform Clapping Music with you. I think that would be tough to do on the spot.
    AR: We can do that offline.
    EL: Yeah, we’ll do that once we hang up.
    AR: As far as foods, I think there are some great pairings of foods with the ergodic theorem. In fact, I think we apply the ergodic theorem often in cooking. You know, you mix stuff up. So one thing I like to do sometimes is make noodles, with a roller thing.
    EL: Oh, from scratch?
    AR: Yeah. You just get some flour, get some eggs, or if you’re vegan, you get some water. That’s the ingredients. You mix it up and you put it through this roller thing, so you can imagine things are getting quite mixed up. What’s really cool, I don’t know if you’ve ever eaten something they call in Italy paglia e fieno, straw and hay.
    EL: No.
    AR: And all it is is pasta colored green, so they put a little spinach in one of them. So you’ve got white and green noodles. So when you cook some spinach, you’ve got your dough. You put some blobs of spinach in. You start mushing it around and cranking it through, and you see the blobs make these cool streaks, and the patterns are amazing, until it’s uniformly, more or less, green.
    EL: Yeah.
    AR: So I’d say, paglia e fieno, we put on some Steve Reich, and there you go.
    EL: That’s great. A double pairing. I like it.
    AR: You can think of a lot of other things.
    EL: Yeah, but in the pasta, you can really see it, almost like taffy. When you see pulling taffy. You can almost see how it’s getting transformed.
    AR: It’s getting all mushed around.
    EL: Thank you so much for talking to me about the Birkhoff ergodic theorem. And I hope you have a good rest of MathFest.
    AR: You too, Evelyn. Thank you.
    [outro]

    Show notes (click here)


    Episode 8 - Justin Curry Dec 07, 2017
    Show notes Episode 8 - Justin Curry Kevin Knudson & Evelyn Lamb Download

    Kevin Knudson: Welcome to MFT. I'm Kevin Knudson, your host, professor of mathematics at the University of Florida. I am without my cohost Evelyn Lamb in this episode because I'm on location at the Banff International Research Station about a mile high in the Canadian Rockies, and this place is spectacular. If you ever get a chance to come here, for math or not, you should definitely make your way up here. I'm joined by my longtime friend Justin Curry. Justin.
    Justin Curry: Hey Kevin.
    KK: Can you tell us a little about yourself?
    JC: I'm Justin Curry. I'm a mathematician working in the area of applied topology. I'm finishing up a postdoc at Duke University and on my way to a professorship at U Albany, and that's part of the SUNY system.
    KK: Contratulations.
    JC: Thank you.
    KK: Landing that first tenure-track job is always
    JC: No easy feat.
    KK: Especially these days. I know the answer to this already because we talked about it a bit ahead of time, but tell us about your favorite theorem.
    JC: So the theorem I decided to choose was the classification of regular polyhedra into the five Platonic solids.
    KK: Very cool.
    JC: I really like this theorem for a lot of reasons. There are some very natural things that show up in one proof of it. You use Euler's theorem, the Euler characteristic of things that look like the sphere, R=2.
    There's duality between some of the shapes, and also it appears when you classify finite subgroups of SO(3). You get the symmetry groups of each of the solids.
    KK: Oh right. Are those the only finite subgroups of SO(3)?
    JC: Well you also have the cyclic and dihedral groups.
    KK: Well sure.
    JC: They embed in, but yes. The funny thing is they collapse too because dual solids have the same symmetry groups.
    KK: Did the ancient Greeks know this, that these were the only five? I'm sure they suspected, but did they know?
    JC: That's a good question. I don't know to what extent they had a proof that the only five regular polyhedra were the Platonic solids. But they definitely knew the list, and they knew they were special.
    KK: Yes, because Archimedes had his solids. The Archimedean ones, you are allowed different polygons.
    JC: That's right.
    KK: But there's still this sort of regularity condition. I can never remember the actual definition, but there's like 13 of them, and then there's 5 Platonics. So you mentioned the proof involving the Euler characteristic, which is the one I had in mind. Can we maybe tell our listeners how that might go, at least roughly? We're not going to do a case analysis.
    JC: Yeah. I mean, the proof is actually really simple. You know for a fact that vertices minus edges plus faces has to equal 2. Then when you take polyhedra constructed out of faces, those faces have a different number of edges. Think about a triangle, it has 3 edges, a square has 4 edges, a pentagon is at 5. You just ask how many edges or faces meet at a given vertex? And you end up creating these two equations. One is something like if your faces have p sides, then p times the number of faces equals 2 times the number of edges.
    KK: Yeah.
    JC: Then you want to look at this condition of faces meeting at a given vertex. You end up getting the equation q times the number of vertices equals 2 times the number of edges. Then you plug that into Euler's theorem, V-E+F=2, and you end up getting very rigid counting. Only a few solutions work.
    KK: And of course you can't get anything bigger than pentagons because you end up in hyperbolic space.
    JC: Oh yeah, that's right.
    KK: You can certainly do this, you can make a torus. I've done this with origami, you sort of do this modular thing. You can make tori with decagons and octagons and things like that. But once you get to hexagons, you introduce negative curvature. Well, flat for hexagons.
    JC: That's one of the reasons I love this theorem. It quickly introduces and intersects with so many higher branches of mathematics.
    KK: Right. So are there other proofs, do you know?
    JC: So I don't know of any other proofs.
    KK: That's the one I thought of too, so I was wondering if there was some other slick proof.
    JC: So I was initially thinking of the finite subgroups of SO(3). Again, this kind of fails to distinguish the dual ones. But you do pick out these special symmetry groups. You can ask what are these symmetries of, and you can start coming up with polyhedra.
    KK: Sure, sure. Maybe we should remind our readers about-readers-I read too much on the internet-our listeners about duality. Can you explain how you get the dual of a polyhedral surface?
    JC: Yeah, it's really simple and beautiful. Let's start with something, imagine you have a cube in your mind. Take the center of every face and put a vertex in. If you have the cube, you have six sides. So this dual, this thing we're constructing, has six vertices. If you connect edges according to when there was an edge in the original solid, and then you end up having faces corresponding to vertices in the original solid. You can quickly imagine you have this sort of jewel growing inside of a cube. That ends up being the octahedron.
    KK: You join two vertices when the corresponding dual faces meet along an edge. So the cube has the octahedron as its dual. Then there's the icosahedron and the dodecahedron. The icosahedron has 20 triangular faces, and the dodecahedron has 12 pentagonal faces. When you do the vertex counts on all of that you see that those two things are dual. Then there's the tetrahedron, the fifth one. You say, wait a minute, what's its dual?
    JC: Yeah, and well it's self-dual.
    KK: It's self-dual. Self-dual is a nice thing to think about. There are other things that are self-dual that aren't Platonic solids of course. It's this nice philosophical concept.
    JC: Exactly.
    KK: You sort of have two sides to your personality. We all have this weird duality. Are we self-dual?
    JC: I almost like to think of them as partners. The cube determines, without even knowing about it, its soulmate the octahedron. The dodecahedron without knowing it determines its soulmate the icosahedron. And well, the tetrahedron is in love with itself.
    KK: This sounds like an algorithm for match.com.
    JC: Exactly.
    KK: I can just see this now. They ask a question, “Choose a solid.” Maybe they leave out the tetrahedron?
    JC: Yeah, who knows?
    KK: You don't want to date yourself.
    JC: Maybe you do?
    KK: Right, yeah. On our show we like to ask our guests to pair their theorem with something.
    JC: It's a little lame in that it's sort of obvious, but Platonic solids get their name from Plato's Timaeus. It's his description of how the world came to be, his source of cosmogeny. In that text he describes an association of every Platonic solid with an element. The cube is correspondent with the element earth. You want to think about why would that be the case? Well, the cube can tessellate three-space, and it's very stable. And Earth is supposed to be very stable, and unshakeable in a sense. I don't know if Plato actually knew about duality, but the dual solid to the cube is the octahedron, which he associated with air. So you have this earth-sky symbolic dualism as well.
    Then unfortunately I think this kind of analogy starts to break down a bit. You have the icosahedron, the one made of triangle sides. This is associated to water. And if you look at it, this one sort of looks like a drop of water. You can imagine it rolling around and being fluid. But it's dual to the dodecahedron, this oddball shape. They only thought of four elements: earth, fire, wind, water. What do you do with this fifth one? Well that was for him ether.
    KK: So the tetrahedron is fire?
    JC: Yeah, the tetrahedron is fire.
    KK: Because it's so pointy?
    JC: Exactly.
    KK: It's sort of rough and raw, or that They Might Be Giants Song “Triangle Man.” It's the pointiest one. Triangle wins every time.
    JC: The other thing I like is that fire needs air to breathe. And if you put tetrahedra and octahedra together, they tessellate 3-space.
    KK: So did they know that?
    JC: I don't know. That's why this is fun to speculate about. They obviously had an understanding. It's unclear what was the depth or rigor, but they definitely knew something.
    KK: Sure.
    JC: We've known this for thousands of years.
    KK: And these models, are they medieval, was it Ptolemy or somebody, with the nested?
    JC: The way the solar system works.
    KK: Nested Platonic solids. These things are endlessly fascinating. I like making all of them out of origami, out of various things. You can do them all with business cards, except the dodecahedron.
    JC: OK.
    KK: It's hard to make pentagons. You can take these business cards and you can make these. Cubes are easy. The other ones are all triangular faces, and you can make these triangular modules where you make two triangles out of business cards with a couple of flaps. And two of them will give you a tetrahedron. Four of them will give you an octahedron. The icosahedron is tricky because you need, what, 10 business cards. I have one on my desk. It's been there for 10 years. It's very stable once it's together, but you have to use tape along the way and then take the tape off. It's great fun. There's this great book by Thomas Hull, I forgot the name of it [Ed note: it's called Project Origami: Activities for Exploring Mathematics], a great origami book by Thomas Hull. I certainly recommend all of that.
    Anything else you want to add? Anything else you want to tell us about these things? You have all these things tattooed on your body, so you must be
    JC: I definitely feel pretty passionate. It's one of those things, if I have to live with this for 30 years, I'll know the Platonic solid won't change. There won't be suddenly a new one discovered.
    KK: Right. It's not like someone's name, you might regret it later. But my tattoos are, this is man, woman, and son. My wife and I just had our 25th anniversary, so this is still good. I don't expect to have to get rid of that.
    Anyway, well thanks, Justin. This has been great fun. Thanks for taking a few minutes out of your busy schedule. This is a really cool conference, by the way.
    JC: I love it. We're bringing together some of the brightest minds in applied topology, and outside of applied topology, to see how topology can inform data science and how algebra interacts in this area, what new foundations we need and aspects of algebra.
    KK: Yeah, it's very cool. Thanks again, and good luck in your new job.
    JC: Thanks, Kevin.
    [outro]

    Show notes (click here)


    Episode 7 - Henry Fowler Nov 16, 2017
    Show notes Episode 7 - Henry Fowler Kevin Knudson & Evelyn Lamb Download

    Evelyn Lamb: Welcome to My Favorite Theorem, the show where we ask mathematicians what their favorite theorem is. I’m your host 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. I had to wear a sweater yesterday.
    EL: Oh my goodness! Yeah, I’ve had to wear a sweater for about a month and a half, so.
    KK: Yeah, yeah, yeah.
    EL: Maybe not quite that long.
    KK: Well, it’ll be hot again tomorrow.
    EL: Yeah. So today we’re very glad to have our guest Henry Fowler on. Henry, would you like to tell us a little bit about yourself?
    Henry Fowler: I’m a Navajo Indian. I live on the Navajo reservation. I live by the Four Corners in a community, Tsaile, Arizona. It’s a small, rural area. We have a tribal college here on the Navajo Nation, and that’s what I work for, Diné College. I’m a math faculty. I’m also the chair for the math, physics, and technology. And my clan in Navajo is my maternal clan is Bitterwater and my paternal clan is Zuni Edge Water.
    EL: Yeah, and we met at the SACNAS conference just a couple weeks ago in Salt Lake City, and you gave a really moving keynote address there. You talked a little bit about how you’re involved with the Navajo Math Circles.
    HF: Yes. I’m passionate about promoting math education for my people, the Navajo people.
    EL: Can you tell us a little bit about the Navajo Math Circles?
    HF: The Navajo Math Circles started seven years ago with a mathematician from San Jose State University, and her name is Tatiana Shubin. She contacted me by email, and she wanted to introduce some projects that she was working on, and one of the projects was math circles, which is a collection of mathematicians that come together, and they integrate their way of mathematical thinking for grades K-12 working with students and teachers. Her and I, we got together, and we discussed one of the projects she was doing, which was math circles. And it was going to be here on the Navajo Nation, so we called it Navajo Math Circles. Through her project and myself here living on the Navajo Nation, we started the Navajo math circles.
    KK: How many students are involved?
    HF: We started first here at Diné College, we started first with a math summer camp, where we sent out applications, and these were for students who had a desire or engaged themselves to study mathematics, and it was overwhelming. Over 50 students applied for only 30 slots that were open because our grant could only sustain 30 students. So we screened the students and with the help of their regular teachers from junior high or high school, so they had recommendation letters that were also presented to us. So we selected the first 30 students. Following that we expanded our math circle to the Navajo Nation public school system, and there’s also contract schools and grant schools. Now we’re serving, I would say over 1,000 students now.
    KK: Wow. That’s great. I assume these students have gone on to do pretty interesting things once they finish high school and the circle.
    HF: Yes. We sort of strategized. We wanted to work with lower grades a little bit. We wanted to really promote a different way of thinking about math problems. We started off with the first summer math camp at the junior high or the middle school level, and also the students that were barely moving to high school, their freshman year or their 10th grade year. That cohort, the one that we started off with, they have a good rate of doing very well with their academic work, especially in math, at their high school and junior high school. We have four that have graduated recently from high school, and all four of them are now attending a university.
    KK: That’s great.
    EL: And some of our listeners may have seen there’s a documentary about Navajo math circles that has played on PBS some, and we’ll include a link to that for people to learn a little bit about that in the show notes for the episode. We invited you here to My Favorite Theorem, of course, because we like to hear about what theorems mathematicians enjoy. So what have you selected as your favorite theorem?
    HF: I have quite a few of them, but something that is simple, something that has been an awe for mathematicians, the most famous theorem would be the Pythagorean theorem because it also relates to my cultural practices, to the Navajo.
    KK: Really?
    HF: The Pythagorean theorem is also how Navajo would construct their traditional home. We would call it a Navajo hogan. The Navajo would use the Pythagorean theorem charting how the sun travels in the sky, so they would open their hogan door, which is always constructed facing east. So once the sun comes out, it projects its energy, the light, into the hogan. The Navajo began to study that phenomenon, how that light travels in space in the hogan. They can predict the solstice, the equinox. They can project how the constellations are moving in the sky, so that’s just a little example.
    EL: Oh, yeah. Mathematicians, we call it the Pythagorean theorem, but like many things in math, it’s not named after the first person ever to notice this relationship. The Pythagorean theorem is a2+b2=c2, the relationship between the lengths of the legs of a right triangle and the hypotenuse of a right triangle, but it was known in many civilizations before, well before Pythagoras was born, a long time ago. In China, India, the Middle East, and in North America as well.
    HF: Yes, Navajo, we believe in a circle of life. There’s time that we go through our process of life and go back to the end of our circle, and it’s always about to give back, that’s our main cultural teaching, to give back as much as you can, back to the people, back to nature, back to your community, as well as what you want to promote, what you’re passionate about, to give back to the people that way. Our way is always interacting with circles, that phenomenon, and how the Navajo see the relationship to space, the relationship to sunlight, how it travels, how they capture it in their hogan. Also they can related it to defining distance, how they relate the Pythagorean theorem to distance as well as to a circle.
    KK: What shape is the hogan? I’m sort of curious now. When the light comes in, what sort of shadows does it cast?
    HF: The Navajo hogan is normally a nine-sided polygon, but it Navajo can also capture what a circle means by regular polygons, the more sides they have, drawing to become a circle. They understand that event, they understand that phenomenon. The nine sides is in relationship to when a child is conceived and then delivered, it’s nine months. The Navajo call it nine full moons because they only capture what’s going on within their environment, and they’re really observant to how the sky and constellations are moving. Their monthly calendar is by full moon. And so that’s how, when the light travels in, when they open that hogan door, it’s like a semi-circle. In that space they feel like they are also secure and safe, and that hogan is also a representation that they are the child of Mother Earth, and that they are the child of Father Sky. And so that hogan is structured in relationship to a mother’s womb, when a child is being conceived and that development begins to happen. Navajos say that the hogan is a structure where in relationship there are four seasons, four directions, and then there are four developments that happen until you enter old age. There will be the time of your birth, the time when you become an adult, mid-life, and eventually old age. So using that concept, when that door is open, they harvest that sunlight when it comes in. Now we are moving to the state of winter solstice. That happens, to western thinking, around December 22. To the Navajo, that would be the 13th full moon, so when that light comes in that day, it will be a repeated event. They will know where. When the light comes into the hogan, when the door is opened, it will project on the wall of the hogan. When it projects on that wall, they mark it off. Every time, each full moon, they capture that light to see where it hits on the wall. That’s how they understand the equinox, that’s how they understand the solstice, in relationship to how the light is happening.
    KK: Wow, that’s more than my house can do.
    HF: Then they also use a wood stove to heat the hogan. There’s an opening at the center of the hogan, they call the chimney. They capture that sunlight, and they do every full moon. Sometimes they do it at the middle of that calendar, they can even divide that calendar into quarters. When they divide it into quarters, they chart that light as it comes in through the chimney. They find out that the sun travels through the sky in a figure eight in one whole year. They understand that phenomenon too.
    KK: Ancient mathematics was all about astronomy, right? Every culture has tried to figure this out, and this is a really ingenious solution, with the chimney and the light. That’s really very cool.
    HF: The practice is beginning not to be learned by our next generation because now our homes are more standardized. We’re moving away from that traditional hogan. Our students and our young people are beginning not to interact with how that light travels in the hogan space.
    KK: Did you live in a hogan growing up?
    HF: Yes. People around probably my age, that was how they were raised, was in a traditional hogan. And that was home for us, that construction. Use the land, use nature to construct your home with whatever is nearby. That’s how you create your home. Now everything is standardized in relation to different building codes.
    EL: So what have you chosen to pair with your theorem?
    HF: I guess I pair my Pythagorean theorem to my identity, who I am, as a Navajo person. I really value my identity, who I am as an indigenous person. I’m very proud of my culture, my land, where I come from, my language, as well as I compare it to what I know, the ancient knowledge of my ancestors is that I always respect my Navajo elders.
    KK: Very cool. Do you think that living in a hogan, growing up in a hogan, did that affect you mathematically? Do you think it sort of made you want to be a mathematician? Were you aware of it?
    HF: I believe so. We did a lot of our own construction, nothing so much that would be store-bought. If you want to play with toys, you’d have to create that toy on your own. So that spatial thinking, driving our animals from different locations to different spots, and then bringing our sheep back at a certain time. You’d calculate this distance, you’d estimate distance. You’d do a lot of different relationships interacting with nature, how it releases patterns. You’d get to know the patterns, and the number sense, the relationships. I really, truly believe that my culture gave me that background to engage myself to study mathematics.
    KK: Wow.
    EL: Yeah, and now you’re making sure that you can pass on that knowledge and that love for mathematics to younger people from your community as well.
    HF: That’s my whole passion, is to strengthen our math education for my Navajo people. Our Navajo reservation is as large as West Virginia.
    EL: Oh, wow, I didn’t realize that.
    HF: And there’s no leader that has stood up to say, “I’m going to promote math education.” Right now, in my people, I’m one of the leaders in promoting math eduction. It’s strengthening our math K-12 so we build our infrastructure, we build our economy, we build better lives for my Navajo people, and that we build our own scientists, we build our own doctors and nurses, and we want to promote our own students, to show interests or take the passion and have careers in STEM fields. We want to build our own Navajo professors, Navajo scholars, Navajo researchers. That all takes down to math education. If we strengthen the education, we can say we are a sovereign nation, a sovereign tribe, where we can begin to build our own nation using our own people to build that nation.
    EL: Wow, that’s really important work, and I hope our listeners will go and learn a little bit more about the Navajo math circles and the work you do, and other teachers and everyone are doing there.
    HF: It’s wonderful because we have so many social ills, social problems among my people. There’s so much poverty here. We have near 50 percent unemployment. And we want my people to have the same access to opportunity just like any other state out there. And the way, from my perspective, is to promote math education, to bring social justice and to have access to a fair education for my people. And it’s time that the Navajo people operate their own school system with their own indigenous view, create our own curriculum, create our own math curriculum, and standardize our math curriculum in line to our elders’ thinking, to our culture, to our language, and that’s just all for my Navajo people to understand their self-identity, so they truly know who they are, so they become better people, and they get that strength, so that that motivation comes. To me, that’s what my work is all about, to help my people as a way to combat the social problems that we’re having. I really believe that math kept me out of problems when I was growing up. I could have easily joined a gang group. I would not have finished my education, my western education, but math kept me out of problems, out of trouble growing up.
    KK: You’re an inspiration. I feel like I’m slacking. I need to do something here.
    EL: Yeah. Thank you so, so much for being on the podcast with us. I really enjoyed talking with you.
    KK: Yeah, this was great, Henry. Thank you.
    HF: You’re welcome.
    [outro]

    Show notes (click here)


    Episode 6 - Eriko Hironaka Oct 26, 2017
    Show notes

    Episode 6 - Eriko Hironaka Kevin Knudson & Evelyn Lamb Download This transcript is provided as a courtesy and may contain errors.EL: Welcome to My Favorite Theorem. I’m your host Evelyn Lamb. I’m a freelance math and science writer based in Paris for a few more days, but after that I’ll be based in Salt Lake City, Utah. And this is your other host. KK: Hi, I’m Kevin Knudson, professor of mathematics at the University of Florida, where it’s raining. It’s been raining for a week. After a spring of no rain, now it’s raining. But that’s OK. EL: I probably shouldn’t tell you that it’s absolutely gorgeous, sunny and 75 degrees in Paris right now. KK: You really shouldn’t. EL: OK, then I won’t. OK. Each episode we invite a mathematician on to find out about their favorite theorem. Today we’re very happy to welcome Eriko Hironaka onto the show. So would you like to tell us a little bit about yourself, Eriko? EH: Yes, thank you, first of all, for having me on this show. It’s very flattering and exciting. I worked at Florida State University for almost twenty years. I was a professor there, and I recently moved to the American Mathematical Society. I’ve been working there for two years. One year, I guess, full time, so far. I work in the book program. I’m somebody who is a mathematician but is doing it from various angles. EL: Yeah, I was really interested in having you on the podcast because I think that’s a cool perspective to have where you’ve been in the research world for a long time, but now you’re also seeing a broader view, maybe, of math, or kind of looking at it from a different angle than before. Do you mind telling us a little bit about what you do as a book person for the AMS? EH: Yeah, what do I do? Actually I was thrown into this job, in a way. They said, OK, you’re going to work in the book program. Your job is basically to talk to people about books, and see if anybody wants to write a book, and if they do, you keep talking with them, and when they finally submit something, you prepare, maybe the real job part is to, once there’s a submission, start it through a review process, then also what’s kind of exciting is to convince the publishing group to actually publish the book. That part requires me to think about how this book fits into mathematics and mathematical literature and then also how much it’ll cost to produce the book and what’s involved in selling the book. Who is the audience and how can it be presented in the best possible way? I think of myself as sort of the connector between the author, who is thinking about the mathematics, and the publishers, who are thinking about. The AMS is a nonprofit, but to cover costs and make this a reasonable project. EL: You see a lot of different aspects of this, then. EH: Yeah, so I don’t know if I was more naive than most mathematicians, but I think most mathematicians don’t think beyond proving theorems and conveying and communicating their ideas to other people. Maybe they also think about what to write on their vita, and things like that. That kind of thing is very different. Right now I don’t really have a reason to keep up my vita in the same way that I used to. That was a big change for me. KK: Right. EH: I still do mathematics, I still do research, give talks, and things like that. I still write papers. But that’s really become something just for me. Not for me, it’s for math, I guess. But it’s not for an institute. KK: It’s not for the dean. EH: It’s not for the dean. Exactly. KK: That’s really liberating, I would think, right? EH: It’s super liberating, actually. It’s really great. KK: Very cool. I dream about that. One of these days. EH: I feel like I’m supporting mathematics kind of from the background. Now I think about professors as being on the battlefield. They’re directly communicating with people, with students, with individuals. And working with the deans. Making their curriculum and program and everything work. EL: So what have you chosen as your favorite theorem? EH: OK, Well, I thought about that question. It’s very interesting. I’ve even asked other people, just to get their reaction. It’s a very interesting question, and I’m curious to know what other people have answered on your podcast. When I think of a theorem I think about not just the statement, but more the proof. I might think of proofs I like, theorems whose proofs I like, or I might think about how this theorem helped me because I really needed something. It’s actually kind of utilitarian, but a favorite theorem should be more like what made you feel great. I have to say for that, it’s a theorem of my own. KK: Cool, great. EH: So I have a favorite theorem, or the theorem that made me so excited, and it was the first theorem I ever proved. The reason it’s my favorite theorem is because of a mixture not just of feeling great that I’d proved the theorem but also feeling like it was a big turning point in my life. I felt like I had proved myself in a way. That’s this theorem, I think of it as a polynomial periodicity theorem, and what it says. Do you want me to say what the theorem is? KK: Yeah, throw it out there, and we’ll unpack it. EH: So the theorem in most generality, it says that if you have a finite CW complex, if you have a sort of nice space, in my case I was looking at quasiprojective varieties, but any kind of reasonably nice space, you can take a sequence of coverings, of regular coverings, corresponding to a choice of map from the fundamental group of the space to some, say, free abelian group, and the way you get the sequence of coverings is you take that map and compose it with the map from that free abelian group to the free abelian group tensored with Z mod n. So if everything is finitely generated, that gives you a surjective map from the fundamental group of your space to a finite abelian group. And now by the general theorem of covering spaces gives you a sequence of finite coverings of your space. And then if you have that space having a natural completion you can talk about natural branch coverings associated to those for each n. My theorem was what happens to the first Betti numbers of these things? The rank of the first homology of these coverings. I showed that this sequence actually has a pattern. In fact, there is a polynomial for every set base space and map from the fundamental group of the base space to a free abelian group, there is a polynomial with possibly periodically changing coefficients so that the first Betti number is that polynomial evaluated at n. KK: Wow. EH: So n is the degree of the covering. The Betti numbers are changing periodically, the polynomials are changing periodically, but it’s a pattern, it’s a nice pattern, and there’s a single polynomial telling you what all of these Betti numbers are doing. EL: So what was the motivation behind this theorem? EH: This problem of understanding the first Betti number of coverings comes from work of Zariski back in the early 1900s. His goal was to understand moduli of plane curves with various kinds of singularities. Simply put, what he did was he tried to distinguish curves by looking at topology, blending topology with algebraic geometry. This was kind of a new idea. This is not very well known about Zariski, but one of his innovations was bringing in topology to the study of algebraic geometry. KK: That’s why it’s called the Zariski topology, right? I don’t know. One assumes. EH: In a way. Not really! KK: I’m not a historian. My bad. EH: He brought geometry topology in. The Zariski topology is more of an algebraic definition. What he did was he was interested, for example, he showed that, what he was interested in when you’re talking about moduli of plane curves is whether or not you can get from one plane curve with prescribed singularities, say a sextic curve, a degree six curve, in C2, in the complex plane, with exactly six simple cusps. So six points in the plane can either lie on a conic or not. General position means it doesn’t lie on lines, doesn’t lie on a conic. But if the six points lie on a conic, it turns out you cannot move within the space of sextics with six cusps to a sextic with six cusps not lying on a conic. KK: OK EH: They’re two distinct families. You’d have to leave that family to get from one to another. You can’t deform them in the algebraic category. To prove this, he said, well, basically, even though the idea of fundamental groups and studying fundamental groups was really new still and was just starting to be considered a tool for knot theory, for example, that came a little bit later. But he said, you can tell they’re different because their topology is different. For example, take coverings. Take your curve, and say it’s given by the equation F(x,y)=0. So F(x,y) is a polynomial. Take the polynomial z^n=F(x,y). You get a surface in three-dimensional space, and now look at the first Betti number of that. So the first Betti number, the first homology, can kind of be described algebraically in terms of other things, divisors and things like that. You can think of it as a very algebraic invariant, but you can also think of it as a topological invariant. Forget algebra, forget complex analysis, forget everything. And he showed that if you take the sextics with six cusps and you took z^n=F(x,y), you get things with first Betti number nontrivial, and by the way, periodically changing with n. In fact, when 6 divides n, it’s nontrivial. It jumps. Every time 6 divides n, it jumps. Otherwise I can’t remember, I think it’s zero. But in the case that the cusps are in general position, the first Betti numbers are always zero. KK: OK. EH: So that must mean that the topology is different. And if the topology is different, they can’t be algebraically equivalent. So that was the process of thinking, that topology can tell you something about algebraic geometry. And that kind of topology is what geometric topologists study now, fundamental groups, etc. But this was all a very new idea. EL: So that’s kind of the environment that your theorem lives in, this intersection between topology and algebraic geometry. EH: That’s right. So my theorem, Sarnak conjectured, I was working on fundamental groups of complements of plane curves, especially with multiple components, for my thesis. And Peter Sarnak was looking at certain problems coming from number theory that had to do with arithmetic subgroups of GL(n) and looking at what happens when you take your fields to be finite, and things like that. You get these finite fields. Somehow in his work, something coming from number theory, he wondered, hearing about what I was doing with fundamental groups and Alexander polynomials, which have to do with Betti numbers of coverings, he asked, “Can you show that the Betti numbers of coverings are periodic or polynomial periodic,” which is that other thing. I thought, OK, I’ll do this, and since I was already working topologically, I could get the topological part by looking at the unbranched coverings, and then I had to complete it. To understand the completion, the rest, there’s a difference between the Betti numbers of the unbranched coverings and the Betti numbers of the branched coverings, to understand that, I needed to understand intersections of curves on the surface, to sort of understand intersection theory of algebraic curves. And these have very special properties, nice properties coming from the fact that we’re talking about varieties. KK: Right. EH: And I used that to complete the proof. It was a real blend of topology and algebraic geometry. That’s what made it really fun. KK: That’s a lot of mathematics going in. And I love your confidence. Peter Sarnak said, “Hey, can you do this?” and you said, “Yeah, I can do this.” EH: Right, well I was feeling pretty desperate. It was really a time of: Should I do math? Should I not do math? Do I belong here? And I thought, “OK, I’ll try this. If it works, maybe that’s a sign.” EL: So what have you chosen to pair with this theorem? EH: As it happens, after I proved this theorem and I showed it to Sarnak, I basically wrote a three-page outline of the proof. I showed it to him, and he looked at it carefully and said, “Yeah, this looks right.” Also, you know, you can feel it when you have it. Suddenly everything has become so clear. I was glowing with this and driving from Stanford to Berkeley, which is about an hour drive, and I usually took a nicer route through the hills to the west, so you can imagine driving with these vales and woods, and it was beautiful sunshine and everything, and the Firebird suite starts out very quiet, and it just perfectly represented what it feels like to prove a theorem. It starts really quiet, and then it gets really choppy and frenzied. KK: And scary. EH: Exactly, scary. The struggling bird, he’s anxious and frightened, really, really unsettling. And then there’s this real gentleness, feeling like it’s going to be OK, it’s going to be OK. But that also is a bit disturbing. There’s something about it that’s disturbing. So it keeps you listening, even though it’s very sweet and the themes are developed, it’s a very beautiful theme. Then there’s this bang and then it becomes really frenzied again, super frenzied, but excited. And then it becomes bolder and bolder. And then that melody comes in, and it starts to really come together. And it starts to feel like you’re running, like there’s a direction, and then finally it gets quiet again. There’s this serenity. And this time the serenity is real. All this stuff has built up to it, and that starts to build and the beautiful theme comes out in the end. It’s just this glorious wonder at the very end. It was like all my excitement was just exemplified in this piece of music. EL: I love that picture of you driving through California, blasting Firebird. EH: Yes, exactly. EL: With this triumphant proof that you’d just done. That’s really a great picture. KK: So my son just finished high school, and he wants to be a composer. He’s going to go to college and study composition. And I actually sort of credit that piece, Firebird suite, as one of the pieces that really motivated him to become a composer. That and Rhapsody in Blue. EH: It really tells a story. KK: Yes, it does. It’s really spectacular. So I think maybe a lot of our listeners don’t know that you have a rather famous father. EH: Yes. KK: Your father won the Fields medal for proving resolution of singularities in characteristic zero, right? EH: Yes. KK: What was that like? EH: Yeah, so I had a really strange relationship with mathematics. Because I grew up with a mathematician father, I avoided math like the plague, you know. Partly because my father was a mathematician, and I thought that was kind of strange, that it didn’t fit in with the rest of the world that I knew. I grew up in the suburbs. It wasn’t a particularly intellectual background. For me, the challenge to my life was to figure out how to fit in, which I was failing at miserably. But I thought that was my challenge. Doing well in math was not the way to fit in in school. I would kind of deliberately add in mistakes to make sure that I didn’t get a good grade. KK: Really? Wow. EH: I would kick myself if I forgot and I would get a high grade and everybody would say, “How did she do that?” You know what I mean? I thought of math as this embarrassment, in a way, to tell the truth, strangely enough. But on the other hand, through my father and his friends and colleagues, I knew that mathematics also had this very beautiful side, and the people who did it were very happy people, it seemed. I saw that other side as well. And I think that was an advantage because I knew that math was really cool. It’s just that that wasn’t my thing. I didn’t want to do that. Also, my teachers were not very exciting. The math teachers seemed to make math as boring as possible. So I had this kind of split personality when it came to math, or split feelin…

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