Incidences Outside of Discrete Geometry (part 2)

You may have noticed that I have a bit of an obsession with geometric incidences. I do believe that incidences are a natural mathematical object that is connected to many different parts of math. This belief seems at least partially justified by the developments of the recent years. Less than two years ago I posted a list of some applications of incidences outside of Discrete Geometry. The purpose of that list was to show how incidences are becoming useful in a variety of fields, such as Harmonic Analysis, Theoretical Computer Science, and Number Theory. It seems that this process did not slow down in the past two years – incidences have continued to demonstrate their usefulness in the aforementioned fields, and there is even a new interest in the subject by model theorists.

This post is part 2 of the list of incidence uses outside of Discrete Geometry. It is just a list of references, and does not include many details. In future posts I might focus on specific applications and provide actual explanations. Hopefully new applications will continue to appear and I’ll have to keep adding more and more parts to this list!

The Kakeya conjecture. Katz and Zahl derived an improved bound for the Kakeya conjecture. Specifically, they improved Wolff’s longstanding bound for the Hausdorff dimension problem in {\mathbb R}^3  . This is the latest in a sequence of Harmonic Analysis works that have strong connections to incidences (see the first part of this list and also below).

Model theory. In Logic, a group of model theorists generalized incidence results to Distal structures. Another similar work extended incidence results to o-minimal structures. In general, there seems to be some interest in generalizing incidence-related problems to various models.

Number theory. A very recent number theoretic result is relying on incidence bounds. Admittedly, I still do not understand what this paper is about, and am hoping to learn that soon.

Algorithms. Moving to Theoretical Computer Science, a recent work analyzes point covering algorithms using incidence results.

Quantum Information. A few years ago, incidences in spaces over finite fields were used to study a problem in Quantum Information. This result is not from the past two years, but I was not aware of it before (thanks Ben Lund).

More Harmonic Analysis. An older survey of Łaba contains a nice review of previous appearances of incidences in Harmonic Analysis. I write “older” although not even a decade have passed. I just mean that this survey appeared before the new era of polynomial methods in Discrete Geometry.

There are obviously more results that are still missing from this list. If you noticed anything that I missed, I would be happy to hear about it.

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Incidences in Higher Dimensions: A Conjecture

I recently added to the incidence theory book two chapters about incidences in {\mathbb R}^d  (Chapters 8 and 9). At the moment incidence bounds in {\mathbb R}^d  are known for several different cases, and it is rather unclear how a general incidence bound in {\mathbb R}^d  should look like. In this post I would like to state what I believe this bound should look like. This conjecture is in part a result of conversations with Joshua Zahl over several years (I do not know whether Josh agrees with everything in this post). The post assumes some familiarity with incidence problems.

zahl_photo
Joshua Zahl. A common name in this blog.

Let us start by stating some known bounds for incidences in {\mathbb R}^d  . The first general incidence bound that relied on polynomial techniques was by Solymosi and Tao.

Theorem 1. Let {\cal P}  be a set of m  points and let {\cal V}  be a set of n  varieties, both in {\mathbb R}^d  . The varieties of {\cal V}  are of degree at most k  and dimension at most d/2  . The incidence graph of {\cal P}\times {\cal V}  contains no copy of K_{s,t}  . Also, whenever two varieties U_1,U_2 \in {\cal V}  are incident to a point p\in {\cal P}  , the tangent spaces of U_1  and U_2  at p  intersect at a single point. Then for any \varepsilon>0

I({\cal P},{\cal V}) = O_{k,s,t,d,\varepsilon}\left(m^{\frac{s}{2s-1}+\varepsilon}n^{\frac{2s-2}{2s-1}}+m+n\right).

While Theorem 1 provides a nice incidence bound, the varieties in it are somewhat restricted. A result of Fox et al. holds for varieties of any dimension and without the restriction on the tangent spaces, at the cost of having a weaker bound.

Theorem 2. Let \cal P  be a set of m  points and let \cal V  be a set of n  varieties of degree at most k  , both in {\mathbb R}^d  . Assume that the incidence graph of {\cal P}\times {\cal V}  contains no copy of K_{s,t}  . Then for any \varepsilon>0

I({\cal P},{\cal V}) = O_{k,s,t,d,\varepsilon}\left(m^{\frac{(d-1)s}{ds-1}+\varepsilon}n^{\frac{d(s-1)}{ds-1}}+m+n\right).

Finally, a result of Sharir et al. provides a stronger bound for the special case of varieties of dimension one that do not cluster in a low degree surface (for brevity, the following is a simplified weaker variant).

Theorem 3. For every \varepsilon>0  there exists a constant c_\varepsilon  that satisfies the following. Let \cal P  be a set of m  points and let \cal V  be a set of n  irreducible varieties of dimension one and degree at most k  , both in {\mathbb R}^d  . Assume that the incidence graph of {\cal P}\times {\cal V}  contains no copy of K_{s,t}  , and that every variety of dimension two and degree at most c_\varepsilon  contains at most q  elements of \cal V  . Then

I({\cal P},{\cal V}) = O_{k,s,t,d,\varepsilon}\left(m^{\frac{s}{ds-d+1} +\varepsilon}n^{\frac{ds-d}{ds-d+1}} + m^{\frac{s}{2s-1}+\varepsilon}n^{\frac{ds-d}{(d-1)(2s-1)}}q^{\frac{(s-1)(d-2)}{(d-1)(2s-1)}}+m+n\right).

The incidence theory book describes in detail how to prove the three above bounds. With these result in mind, we are now ready to make a somewhat vague general conjecture.

Conjecture 4. Let \cal P  be a set of m  points and let \cal V  be a set of n  varieties of degree at most k  and dimension d'  , both in {\mathbb R}^d  . Assume that the incidence graph contains no copy of K_{s,t}  and that the varieties of \cal V  satisfy some “reasonable conditions”. Then for any \varepsilon>0

I({\cal P},{\cal V}) = O_{k,s,t,d,\varepsilon}\left(m^{\frac{sd'}{ds-d+d'}+\varepsilon}n^{\frac{ds-d}{ds-d+d'}} + m + n\right).

Note that we already have three cases of conjecture 4:

  • Theorem 1 obtains the conjecture for varieties of dimension d/2  .
  • Theorem 2 obtains the conjecture for varieties of dimension d-1  .
  • Theorem 3 obtains the conjecture for varieties of dimension 1  .
For varieties of dimension smaller than d/2  , the proof of Theorem 1 projects the configuration to a space of dimension that is twice the dimension of the varieties (forcing the dimension of the varieties to be exactly half the dimension of the space). This seems to be an inefficient step, which makes it likely that the theorem is not tight for varieties of dimension smaller than d/2  . Indeed, Theorem 3 already obtains a stronger bound for the case of varieties of dimension one. For similar reasons, the proof of Theorem 2 seems not to be tight for varieties of dimension smaller than d-1  .

A recent work reduces the distinct distances problem in {\mathbb R}^d  to an incidence problem between points and (d-1)  -dimensional planes in {\mathbb R}^{2d-1}  . Combining this reduction with the bound stated in Conjecture 4 would lead to an asymptotically tight bound for the distinct distances problem in dimension d\ge3  . Other problems also reduce to incidence problems with the same dimensions. Thus, the case of d' = (d-1)/2  (for odd d  ) seems to be a main open case.

While conjecture 4 is known for the cases of varieties of dimension 1,d/2  , and d-1  , so far all of the other cases are open. The bound in the conjecture was not obtained by interpolating the three known cases — there is a better approach that leads to it. Recall that in the polynomial partitioning technique we partition {\mathbb R}^d  into cells, bound the number of incidences in each cell, and then bound the number of incidences that are on the partition (not in any cell). The bound stated in Conjecture 4 is obtained by applying this technique while ignoring the incidences on the partition (since bounding the number of incidences in the cells is much easier).

Recently discovered configurations of points and varieties achieve the bound of the conjecture up to extra \varepsilon  ‘s in the exponents. Thus, in its most general form the bound of the conjecture is tight. However, these constructions give a tight bound only for certain families of varieties of dimension d-1  , for certain ranges of m  and n  , and when s=2  . It seems plausible that the bound of the conjecture is not tight in some other interesting cases. In particular, in {\mathbb R}^2  a stronger bound is already known when s\ge 3  , and it seems reasonable that the same technique would also work for varieties of dimension one in {\mathbb R}^d  . At the moment, it is difficult to guess what should happen with varieties of dimension larger than one. Either way, Conjecture 4 seems to be a reasonable bound for the limits of the current polynomial partitioning technique. It seems that this specific technique could not yield better bounds without major changes.

Let us briefly discuss what the expression “reasonable conditions” in the statement of Conjecture 4 means. We already have two examples of conditions that are considered reasonable:

  • A non-clustering condition: Not too many varieties of \cal V  are contained in a common higher-dimensional variety. For example, this restriction was used in Theorem 3, and more famously in the Guth–Katz proof of the planar distinct distances problem.
  • A transversality condition: When two varieties meet at a point p  , their tangent spaces at p  intersect only at one point. This condition was used in Theorem 1.
It is not clear what the “natural” restrictions are. For example, when studying incidences with two-dimensional planes in {\mathbb R}^4  most works rely on the transversality condition. In this case, the condition is equivalent to asking every two planes to intersect in at most one point. I recently noticed that the same incidence bound holds with a much weaker restriction of not too many planes in a hyperplane.

There is more to say about Conjecture 4, but this post is already getting longer than I intended.

The k-set problem

The k  -set problem is a classic open problem in Combinatorial Geometry, which is considered similar in spirit to incidence problems and to distance problems. While in recent years algebraic techniques led to significant progress in incidence and distance problems, so far none of the new methods were applied to the k  -set problem. This post briefly introduces the problem, and describes a way of reducing it to an incidence problem. I hope that it will get someone to think of the k  -set problem in an algebraic context and maybe come up with some new observations.

Let {\cal P}  be a set of n  points in {\mathbb R}^2  , and let 1\le k\le n/2  be an integer. A k  -set of {\cal P}  is a subset {\cal P}'\subset {\cal P}  of k  points such that there exists a line that separates {\cal P}'  from {\cal P}\setminus{\cal P}'  . That is, {\cal P}'  is on one open half-plane defined by the line, while {\cal P}\setminus{\cal P}'  is on the other half-plane. The following figure depicts two 5-sets of a set of 12 points.

5sets.eps

The k  -set problem asks for the maximum number of k  -sets that a set of n  -points in {\mathbb R}^2  can have. As a first silly example, note that the maximum number of 1-sets is exactly n  . It is not difficult to show that we may assume that no three points are collinear (specifically, perturbing the point set cannot significantly decrease the number of k  -sets).

The number of subsets of k  points of {\cal P}  is \Theta(n^k)  , so this is a straightforward upper bound for the maximum number of k  sets. However, we can easily obtain a significantly stronger upper bound. Consider a k  -set {\cal P}'\subset{\cal P}  that is separated by a line \ell  . We translate \ell  until it is incident to a point p\in {\cal P}'  and then rotate \ell  around p  until it is incident to a second point of {\cal P}  (not necessarily in {\cal P}'  ). For example, see the figure below. Thus, to find all of the k  -sets of {\cal P}  it suffices to consider every line that is incident to two points of {\cal P}  . Since there are O(n^2)  such lines, this is also an upper bound for the number of k  -sets.

kSetLineChange.eps

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Additive Energy of Real Point Sets

Over the years, more and more interactions between Discrete Geometry and Additive Combinatorics are being exposed. These include results such as the Green–Tao ordinary lines theorem and Solymosi’s sum-product bound. One reason for this connection is that both fields study the structure and symmetries of various objects (such as sets of points or subsets of additive groups). In this post I will discuss one of the simplest connections between the two fields — studying the additive energy of a set of points in a real space {\mathbb R}^d  . The main goal of the post is to present two open problems that involve the additive energy of such sets. I heard one of these problems from Nets Katz and the other from Ciprian Demeter. In future posts we might discuss more involved interactions between the two fields.

demeterckatz
Ciprian Demeter and Nets Katz.

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Incidences Outside of Discrete Geometry

Starting the 1980’s, more and more applications of geometric incidences have been found in discrete geometry. By now, one can arguably claim that there are countless such applications. More surprising are the applications of incidences outside of discrete geometry. In the past decade such applications have been discovered in harmonic analysis, theoretical computer science, number theory, and more. This post is my attempt to list these applications. If you are familiar with additional applications that I did not include, I’d be very interested to hear about them (in the comments below or by email).

Additive combinatorics: One of the main milestones in the study of the sum-product problem is a seminal paper by Elekes, in which he reduced the problem to a point-line incidence problem in {\mathbb R}^2  . This led to a variety of results in additive combinatorics that rely on incidences. Tao and Vu’s additive combinatorics book contains a full chapter that is dedicated to incidences. Konyagin and Shkredov’s recent improvement of the sum-product bound also relies indirectly on incidences (to bound the number of collinear triples in a lattice). For more examples, see here and here. Also, several additive combinatorics results in finite fields rely on incidence bounds in finite fields (e.g., see this paper).

Fourier restriction problems: Bourgain and Demeter rely on incidences to derive bounds for the discrete Fourier restriction to the four and five dimensional spheres. Incidences also appear in several related papers by the same authors (e.g., see here and here).

Number theory: A recent paper of Bombieri and Bourgain studies a type of additive energy of the Gaussian integers by relying on incidences with unit circles in {\mathbb R}^2  .

Error correcting codes: A family of papers by Dvir, Saraf, Wigderson, and others use incidences to study error correcting codes. For example, see this paper and this paper. These papers rely mainly on Sylvester-Gallai problems, which do not exactly fit the standard incidence problem formulation. Still, the authors of these paper and others consider these as proper incidence problems.

Extractors: Yet another novel use of incidences by Jean Bourgain. Bourgain relied on a finite field point-line incidence bound to build 2-source extractors. Recently this result has been superseded, as far as I understand without relying on incidences in any way.

Minors of totally positive matrices: Farber, Ray, and Smorodinsky used incidences to bound the number of times that a d\times d  minor can repeat in d\times n  a totally positive matrix.

It might also be interesting to state results that do not rely on incidences but do rely on the same polynomial partitioning technique (applied in the same way):

More restriction problems: Guth recently relied on polynomial partitioning to derive improved restriction estimates for smooth compact surface in {\mathbb R}^3  with strictly positive second fundamental form.

Range searching algorithms: Agarwal, Matoušek,and Sharir used polynomial partitioning to derive range searching algorithms for semialgebraic sets. A later simplification of this result, also based on polynomial partitioning, was derived by Matoušek and Patáková.

Any comments, corrections, and additions to the above list are welcome.

Incidences: Lower Bounds (part 8)

We continue to survey the known lower bounds for incidence problems (the previous post in this series can be found here). After a couple of posts in {\mathbb R}^3  we now return to {\mathbb R}^2  , to introduce a new technique that I recently learned about. This technique was discovered by Jozsef Solymosi, and is described in a work of Solymosi and Endre Szabó that is unpublished at this point. As seems to often be the case with results of Solymosi, it is quite simple and elegent. In {\mathbb R}^2  this technique yields bounds that can also be obtained from Elekes’ technique (discussed in a previous post), but in higher dimensions it leads to new bounds that are also tight (which would hopefully discuss in a future post). I would like to thank Jozsef Solymosi for allowing me to describe his technique in this blog, and to Frank de Zeeuw for discussions that led to this post.

Solymosi
Jozsef Solymosi.

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Incidences: Lower Bounds (part 6)

Last year I surveyed the known lower bounds for incidence problems in the plane (click here for the previous post in the series). I now return to this series of posts to survey the lower bounds that are known in higher dimensions.

From what is already known about incidences with curves in {\mathbb R}^d  , it seems likely that the maximum number of incidences is usually obtained when the points and curves lie in a constant-degree two-dimensional surface. For example, Guth and Katz proved that the maximum number of point-line incidences in {\mathbb R}^3  is obtained when the points and lines are in a common plane. While incidences with general curves are not fully understood even in the plane, various recent results hint that this is also the case for general curves in {\mathbb R}^d  (for example, see here and here).

Due to the above, incidences with curves in {\mathbb R}^d  are usually studied with a restriction on the number of curves that can be contained in various types of constant-degree surfaces; another reason for studying such restrictions is that they arise from interesting problems. For example, Guth and Katz proved the following theorem.

Theorem 1. Let \cal P  be a set of m  points and let \cal L  be a set of n lines, both in {\mathbb R}^3  , such that every plane contains O(\sqrt{n})  lines of \cal L  . Then

I({\cal P},{\cal L}) = O\left(m^{1/2}n^{3/4}+n+m\right).

Currently, all of the known lower bounds for incidences with curves in {\mathbb R}^d  are simple extensions of the planar bounds that we studied in the previous posts. In the current post we only present one such bound. Specifically, we extend Elekes’ planar construction to show that Theorem 1 is tight. The following posts will focus on the more challenging issues that arise for incidences with higher-dimensional objects.

Claim 1. Consider integers m  and n  that satisfy m \ge 4\sqrt{n}  and m\le n^{3/2}  . Then there exist a set \cal P  of m  points and a set \cal L  of n  lines, both in {\mathbb R}^3  , such that every plane contains O(\sqrt{n})  lines of \cal L  and

I({\cal P},{\cal L})= \Theta\left(m^{1/2}n^{3/4} \right).

Proof.     Set k = m^{1/2}/(2n^{1/4})  and \ell = \sqrt{2}n^{3/8}/m^{1/4}  , and let

{\cal P} = \left\{(r,s,t)\in {\mathbb N}^3 : 1\le r \le k \ \text{ and } \ 1\le s,t \le 2k\ell \right\}.

For our set of lines, we take

{\cal L} = \left\{y-ax-b,z-cx-d : 1 \le a,c \le \ell \ \text{ and } \ 1\le b,d \le k\ell \right\}.

First, notice that we indeed have

|{\cal P}| = k (2k\ell)^2 = 4k^3 \ell^2 = 4 \cdot \frac{m^{3/2}}{8n^{3/4}} \cdot \frac{2n^{3/4}}{m^{1/2}} = m,
|{\cal L}| = k^2\ell^4 = \frac{m}{4n^{1/2}} \cdot \frac{4n^{3/2}}{m} = n.

For any line \gamma \in {\cal L}  and 1\le r \le k  , there exists a unique point in \cal P  that is incident to \gamma  and whose x  -coordinate is r  . That is, every line of \cal L  is incident to exactly k  points of \cal P  . Thus, we have

I({\cal P},{\cal L}) = k \cdot n =  \frac{m^{1/2}}{2n^{1/4}} \cdot n= \frac{m^{1/2}n^{3/4}}{2}.

It remains to verify that every plane contains O(\sqrt{n})  lines of \cal L  . We first consider a plane h  that is defined by an equation of the form y=sx+t  (that is, a plane that contains lines that are parallel to the z  -axis). Such a plane h  contains exactly the lines that have a=s  and b=t  in their definition in \cal L  . There are k\ell^2= \Theta(\sqrt{n})  such lines.

Next, consider a plane h  that is not defined by an equation of the form y=sx+t  . In this case, for every choice of a,b  , the plane h' =Z(y-ax-b)  intersects h  in a unique line. That is, for every choice of a,b  as in the definition of \cal L  , there is at most one line of \cal L  with these parameters that is contained in h  . Thus, h  contains k\ell^2= \Theta(\sqrt{n})  lines of \cal L  .