arutar

Hong Wang and Josh Zahl proved something a bit stronger, namely that the Kakeya conjecture holds for families of tubes satisfying the "Convex Wolff Axioms". From the outside this looks like a weird technical detail but if you unpack this you get an exceptional example of 'the journey is worth more than the destination'.

The idea for resolving Kakeya in R3 originates in the work of Jean Bourgain and a connection to the discretized sum-product phenomenon (the idea, in R, that "sum" and "product" are geometrically incompatible). This approach is summarized in Terry Tao's blog post from 12 years ago now [1].

Basically, the efforts to make this approach work resulted in the development of an entirely new and extraordinarily active subfield that one might call "continuous incidence geometry". This led to ideas like restricted projection theory (with spectacular applications in homogeneous dynamics and number theory), decoupling (another one of Thomas Wolff's ideas, and was realized by Bourgain and Demeter), the resolution of the Furstenberg set theorem, etc. There are very far-ranging applications, some of which even appeared on HN, and which a priori look totally unrelated, like the Heilbronn Triangle problem [2]

I know this is out of the context of most here on HN but let me say it in short: the development of the sum-product approach to Kakeya has resulted in a huge improvement of our understanding of the fundamental additive and multiplicative structure of Euclidean space.

OpenAI's proof of local smoothing in Rd shortcuts this entire matter. Don't get me wrong, the proof is phenomenal, and it's amazing that Local Smoothing admits a short, essentially self-contained proof (only uses some facts about elliptic PDEs which I can't comment about unfortunately since it isn't my area).

Hong Wang didn't win the fields medal for proving Kakeya in three dimensions (only). She won because of her incredible contributions to the development of continuous incidence geometry. The proof of local smoothing certainly contains a lot of very interesting insights into the wave equation but, if this proof had appeared in 2014 just like this, I do not think we would have had the same amount of development.

To me, this is the heart of the matter. For mathematicians, only having these incredible new proofs with no "social consequences" would be extraordinary. However, if we are not careful, the idea that math is "solved" will degrade the mathematics tradition in its own right. Where will be in 10 years, in 50 years? Humans, by virtue of being much worse at computations than computers, must build the "correct" abstractions in order to discover new mathematics. If this process is somehow lost, independently of the computer's ability to prove an infinite tower of new results, the mathematics tradition will suffer for it.

1. One can ask the same problem but for k-gons instead of triangles.

2. Given a set of point-line pairs (x1, l1), ..., (xn, ln) [[that is, each xj lies in the line lj]], consider the smallest distance between some xi and lj where i != j. Then as in Heilbronn's problem we want configurations so that this smallest distance is as large as possible.

In 2 here we already see a key feature of 'incidence lower bounds' problems: we need to assume some initial 'trivial incidences' for the problem to make sense at all. If we didn't require them; we could put all the points at the top, and the lines at the bottom, and call it a day! The 'trivial incidences' force the points and lines to be spatially mixed; then we want to find a 'non-trivial incidence'.

Asymptotics for problem 1 are very open (seems decently harder than Heilbronn) but problem 2 was recently solved by Cosmin [1]

Actually, information about (2) immediately gives you something about the Heilbronn problem: take your n points, and use them to define n/2 lines. This gives a family of n/2 points and n/2 lines (forgetting about the 'other' point on each line). Apply the best answer you get to (2), to find a point of distance r to some line. Since that line originally came from two other points, you get a triangle of area ~ r. This is where the best known asymptotics for Heilbronn's problem come from.

From a pure mathematics standpoint, I am most interested in asymptotics (what happens as n becomes very large).

Some tidbits which might be interesting:

* Here's an argument saying there must always be a triangle of area less than about 1/n. Divide the unit square into n/3 vertical strips. By the pigeonhole principle one of the strips must contain three points. The strip has area about 1/n, so the triangle also has area at most 1/n.

* In contrast, the best known lower bound is something like (log n)/n^2 - very far from 1/n.

* After quite a bit of work by a number of authors, Komlós, Pintz & Szemerédi proved in 1981 an upper bound essentially of the form n^(-8/7), still quite far from the n^2 lower bound!

* Remarkably, there was no progress for over 40 years, until a few years ago two PhD students at MIT (Alex Cohen and Dima Zakharov) along with Cosmin Pohoata beat this upper bound by some small factor, and then later improved it to n^(-7/6) a year or so later. (See [1] for an overview of their work.)

* This problem is related to a more general family of incidence geometry problems called 'lower bounds for incidences': given some collection of geometric objects (say, points and lines), under what conditions can we guarantee that there are in fact more 'almost incidences' than we originally expect?

Topological dimension is indeed something one can define: e.g. the Koch snowflake [1] or the graph of the Weierstrass function [2] have topological dimension 1. Actually, the first is homeomorphic to the unit circle and the second is homeomorphic to real line. It's great if you are doing topology and you only care about how things look like up to homeomorphism. But if you have metric structure (and you care about it), it is not so useful.

Minkowski dimension is certainly easy to define but it has some problems: sets which are "very small" (like a sequence `1/log(n)`) can have Minkowski dimension 1. The article has a minor technical oversight: the limit certainly does not need to exist. Minkowski defined it as the limit supremum of the sequence (actually, he defined it in terms of the decay rate of the size of the neighbourhood of the set, but this is equivalent). But one could analogously define a "lower" variant by taking the limit infimum instead.

Hausdorff dimension is not discussed in this article, but it is probably the most "robust" notion of dimension one can define. The Hausdorff dimension of any sequence is 0. But even then, lots of sets with Hausdorff dimension 1 can be very small, like the fat Cantor set which has dimension 1 but has length 0 [3]. So this 'dimension' does not necessarily line up with the intuition for "1-dimensional" in esoteric circumstances.

But even Hausdorff / Minkowski dimension does not capture the essence of some matters. For example, one might be interested in when a certain space can be mapped into another space without too much distortion (let's say by a map which respects the metric, like a bi-Lipschitz map). It can easily happen that a set has small (finite) Hausdorff or Minkowski dimension, but it cannot be embedded in a non-distorting way in any finite dimensional Euclidean space. This happens for instance with the real Heisenberg group [4]. If you are interested in this type problem then you want something like Assouad dimension [5].

The moral of the story is: the correct notion of dimension depends critically on what you want to do with your notion of 'dimension'. For sets which are very nice (smooth manifolds) all "reasonable" notions of dimension will coincide with what you expect; but beyond this there is an infinite zoo of ways to define dimension which are all reasonable in various ways, but capture genuinely different notions of 'size'.

I visited Josh at UBC last year around this time and I recall asking him if he thought Kakeya in dimension 3 would be solved soon. I remember that he believed it would be (though perhaps he was worried by someone other than Hong and himself). In the end they were able to complete the proof themselves.

Hong is probably quite a serious candidate for the fields medal because of this. She has already made impressive progress on problems in harmonic analysis and geometric measure theory and she is one of few people has a firm foothold in both fields at the same time.

The quanta article talks about a 'tower of conjectures' in harmonic analysis; at the top of the tower is the so-called "local smoothing conjecture" (a conjecture about how much waves, such as 'idealized' sound waves, can amplify from some initial configuration when averaged over time). A Kakeya set is a certain type of geometric obstruction to local smoothing; resolving the full conjecture also requires handling so-called 'oscillatory' obstructions. In dimension 2 + 1 (2 spatial and 1 time dimension) the local smoothing was only recently resolved (also by Hong and co-authors [3]); even though the corresponding result for Kakeya sets in dimension 2 has been known for over 40 years.