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Kevin Knudson: Welcome to My Favorite Theorem, the math podcast with no quiz at the end. I am one of your hosts, Kevin Knudson, professor of mathematics at the University of Florida, and your other host is…



Evelyn Lamb: Hi, I'm Evelyn Lamb, a freelance math and science writer in Salt Lake City, Utah, where we sadly are past our beautiful, not too hot spring and fully into summer. So we enjoyed it while it lasted. I didn't have to turn on any air conditioning until after the start of July.




KK: I think we started air conditioning in March.




EL: Slightly different.




KK: Little different vibe down here in Florida, but that's where we are. So anyway, it's summertime here, which means that there are tumbleweeds rolling through my department and I'm answering a few emails a day and trying to work, trying to do math. And boy, sometimes it's hard, you know, but sometimes it isn't. So. Anyway, so today, though, we are — this is great — we are very pleased to welcome Tatiana Toto, who will introduce herself and let us know what she's all about.




Tatiana Toro: Thank you very much for the invitation. I'm very glad to be here. And in fact, I'm very glad to see Evelyn's cloud that I had heard about in other podcasts. So I'm Tatiana Toro. I'm a mathematician at the University of Washington, where I have been a faculty member since 1996. And currently I am the director of the Simon's Lab for Mathematical Sciences Institute, formerly known as MSRI. And I'm in Berkeley, California, and summer hasn't arrived yet.




KK: It never will.




EL: Yeah, that’ll be November, right?




KK: I had actually forgotten that the name of MSRI had changed to the Simon's business. That’ll take some getting used to. I think I mentioned before we started talking, I spent a semester there, way back in 2006, and my son came with me, and my wife did too, and he was seven at the time. And now he's an adult living in Vancouver. It's weird how things change. I love that building, though. And the panoramic view you have the bay, and you can watch the fog roll in through the gate at tea time. It’s just a really wonderful place. So congratulations. How long have you been director? Has it been a year yet?




TT: It’s almost a year, a year August first.




KK: Yeah. That's fantastic. What a terrific position. And I'm glad that you're willing to take it on. Do you split your time between Berkeley and Seattle? Or are you mostly in Berkeley these days?




TT: I am mostly in Berkeley. My students are still in Seattle, so I see them mostly on Zoom. But once in a while on a Friday, in Seattle.




KK: Oh, so you go there. You don't fly them down?




TT: Some of them have come, actually one of them this year to the summer school.




KK: All right. So what is this podcast about? Favorite theorems. And you told us yours ahead of time, but we'll let you share. What is your favorite theorem?




TT: Okay, so my favorite theorem is the Pythagorean theorem, and I know that everybody's gonna say what on earth are you talking about?




EL: No, I really, really love this choice. And, you know, I've said this on many other iterations of this podcast, but I love that, you know, we'll get things that span the gamut from Pythagoras theorem, or the infinitude of primes, or something like that, all the way up to something that you, you know, you need to have been researching for 20 years in some very ultra-specific field to even understand, and so, you know, it just like shows how math connects with us in different ways at different times in our lives, and how we can appreciate some maybe things that seem very simple about math, even when we have had math careers for for many years. So yeah, tell us about how did you end up settling on the Pythagoras theorem?




TT: So, actually, it has played a very important role in my career. Like, when I describe it to my students, when I'm teaching a graduate class and I talk about the some of the theorems I'll describe in a minute, I tell them, you know, one of the key ideas in my thesis was the Pythagorean theorem. So let me explain. It appears in many other results in this area of geometric analysis. So for example — let me give you two examples. So what was my thesis about? You have a surface, a blob in space, and you're trying to — two dimensions in R3 — and you're trying to understand if you can find a parameterization, which means a good way to describe it in terms of the plane. So can you deform the plane in a nice way so that it covers the surface? And a nice way means that distances are not changed too much. So I had some specific conditions for this surface, and the answer, the key, is in the situation I was looking at, yes, you could do it. And when you go and deeply look at what makes this possible, it is the Pythagorean theorem because the basic point is that if you can control how distances are distorted, you can control how the whole shape is mapped from the plane. And at the time, it looked like a curiosity. You know, I graduated many years ago. At the time, a few years earlier, Peter Jones had solved the analyst’s traveling salesman problem, which I'm gonna — just in general terms, let's imagine you have a lot of points in a square, and you're trying to understand whether you can pass a curve of finite length to all of these points. You're going to tell me, “If they’re finite, of course you can.” But you want to do it in an efficient way, in a way that doesn't depend on the number of points. And so he had found the condition that told you if this condition is satisfied, then yes. And there's not an algorithm, that doesn't exist yet, that tells you what's the best curve, but there's a curve, and he tells you that the length is no more than something. And what's behind that is the fact that if you have a straight triangle that has sides, A and B, and the other one is B, A squared plus B squared equals C squared. And it really is understanding that. And there's another important thing, the fact that the square root also plays an important role in these, but really, really, if you ask me, “What are the tools you need in this area?” I'll tell you how the square root behaves in the Pythagorean theorem, and then a couple of good ideas and you're able to reconstruct the whole thing.




KK: I’m now curious about this traveling salesman problem. So there's no algorithm though?




TT: No, there's no algorithm. I used the word analyst’s traveling salesman problem because the analyst wants to know whether you can pass a curve of finite length. Maybe you can say you're not ambitious enough. You don't want the shortest possible curve. To build the shortest curve, there’s no algorithm. And the construction of Peter Jones builds a curve, but it's not necessarily the best one.




KK: Sure. Yeah.




TT: It doesn't tell you it tells you the length is no more than D. But it's not. Yeah, no.




EL: Yeah. I'm trying to remember if, like, I think there probably are some algorithms or some, like results that say like, you can get within a certain percentage of something. But yeah, the algorithm for the actual fastest path doesn't exist yet. Which is, you know, it's one of those things, it's like, huh, that's kind of surprising that we don't have a way to do that yet. Just means that there's still work to be done. Still jobs out there for mathematicians.




KK: Well, because the combinatorial on the graph theory one is, is NP complete, right? I mean, yeah. So that that are NP-hard, or whatever. NP-something. I've never been clear about the differences. But is this one known to be that too?




TT: I believe.




KK: Okay. All right.




TT: But you can construct — you know, so this was what was interesting about the problem, the result of Peter Jones, is that — the result of Peter Jones, and I have to say, I was very ignorant of that result, which had just happened a few years prior to my thesis. I have to remind the young audience that at the time, there was no internet the same way, and there was no arXiv, and you know, there was no Zoom. And then Peter Jones had a couple of postdocs at Yale, Stephen Semmes and Guy David, who started working on this. And the truth is, may I tell story about my thesis?




EL: Yeah.




KK: Please do.




TT: So my thesis came out of misunderstanding. I went to my advisor, and I showed that these surfaces that I was looking at, which were some that he had looked at, that there was this property about distances over the surfaces, like if an ant traveled on the surface between two points, you know, taking the shortest path, it was comparable to the Euclidean distance. And so I went to my advisor, Leon Simon, and I told him, you know, I've been able to do this about these surfaces. And then he told me, oh, then I guess they have about they admitted bilipschitz parameterization, which is this good description. So okay, so I went to the library, and I looked through every possible book that I could find, and I couldn't find that. So I went back two weeks later and asked if he’d mind giving me a reference for this results, and he said, oh, I don't have a reference. That must be true.




KK: It must be true.




TT: And that became my thesis problem. And then, oh, there were many iterations of attempts. And I could do specific cases, but I could not do the general case. And on May of my fourth year, finally, somebody gives a colloquium where he talks about good parameterizations. And he talks about things like what I was thinking. I was thrilled. I mean, I th