Incidences: Open Problems (part 2)

We now continue our journey of seeing how we still don’t know much about geometric incidences. So far, we looked at two main problems concerning incidences with curves in the plane (see the first post of the series). It might make sense to move to study incidences in higher dimensions. Instead, we are now regressing to discuss a problem about incidences with lines in the plane.

Problem 3. Structure for point-line incidences.

The exact asymptotic bound for point-line incidences in {\mathbb R}^2  was derived in the early 1980’s. Although several decades have passed, we still know relatively little about the point-line configurations that lead to many incidences. This is the structural problem: characterizing the point-line configurations that achieve the asymptotically maximal number of incidences.

It is not surprising that we do not know much about the structural problem, since this is the case for most problems in this part of discrete geometry – even after the extremal bound is obtained, we are not able say much about the structure of the extremal solutions. The major exception that comes to mind is the Green-Tao structural result for ordinary lines.

Back to point-line incidences in {\mathbb R}^2  , consider the case of n  points and n  lines. The Szemerédi–Trotter theorem states that the maximum number of incidences in this case is \Theta(n^{4/3})  . We have two constructions that achieve this bound: The original construction of Erdős and a simplified construction by Elekes. The points of the first construction are a \sqrt{n}\times \sqrt{n}  section of the integer lattice {\mathbb Z}^2  . The points in the second construction are an n^{1/3}\times n^{2/3}  section of {\mathbb Z}^2  (see figure below). One can further play with these constructions by applying projective transformations and taking subsets of the lattice.

ElekConst

Here are some structural question one might ask about point-line configurations with \Theta(n^{4/3})  incidences:

  • Are \sqrt{n}\times \sqrt{n}  and n^{1/3}\times n^{2/3}  the only lattice sizes that can achieve \Theta(n^{4/3})  incidences? For example, can we use an n^{2/5}\times n^{3/5}  section of {\mathbb Z}^2  ? Is there a continuous spectrum of lattice sizes or are there only a few sporadic sizes?
  • Must there always be a line that contains \sqrt{n}  of the points? (not necessarily a line from the set of n  lines). It is easy to show that there must exist a line containing n^{1/3}  points. I am not aware of any stronger bound for this problem.
  • Must we rely on a section of {\mathbb Z}^2  ? (possibly with a projective transformation and removing some points) Are there other lattices that work? Are there constructions that do not come from lattices?

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Updates

I did not post anything for almost five months – life has been very busy lately! I hope to get back to posting regularly relatively soon. In the meantime, I wanted to at least have a brief updates post.

I just made a revision of my book about incidences and polynomial methods. Joshua Zahl and I have been running a polynomial methods summer school for graduate students, at MSRI. This led to several topics being added to the book, such as a proof of the cap set theorem and a sum-product bound over finite fields. I also added many exercises, with a focus on clever elegant problems whose solution is not too technical. Many of those exercise have been carefully checked by the participants of the summer school 🙂

MSRI

If you’d like to see more from the summer school, you can now watch close to 25 hours of Joshua Zahl and myself talking about polynomial methods. Starting here. We were lucky to have Marina Iliopoulou and Cosmin Pohoata helping us run this program. And also lucky to have a group of impressive graduate students participating and solving all of our weird exercise!

Our REU program for this summer is getting close to its end. I am amazed by the amount of strong results this summer’s participants produced. Once some of these results will become available online, this would be a good topic for a separate post.

IMG-0217.JPG

I plan to soon write about several interesting events that we will be holding this academic year, upcoming hiring, and other news. I just need some time!

Incidences: Open Problems (part 1)

The past decade brought us several breakthroughs in the study of geometric incidences. Most importantly, Guth and Katz introduced polynomial partitioning, and this has become the main technique for studying incidences. The recent breakthroughs sometimes leads to a wrong impression about the state of this field. Actually, most of the main incidence problems are still wide open. At least one of the biggest incidence problems has been completely stuck since the early 1980’s.

This leads me to something that has been bothering me for a while (but probably not a single other person in the world…) For some reason, one can find the following statement in the Wikipedia page for the Szemeredi-Trotter theorem.

WikiST

Solymosi and Tao indeed obtained an impressive and near sharp bound for an incidence problem. But it was not a general bound for points and varieties. Most incidence problems involving algebraic varieties in higher dimensions remain wide open. (fixed. Thank you David Eppstein!)

This post is the first of a series which will survey some of the main open problems involving incidence geometry. This series will illustrate how much we do not know about geometric incidences. If you are an outsider, you might start to look down at us incidence researchers. Over 35 years have passed since the Szemeredi-Trotter theorem, and since then we managed to resolve very few other incidence problems.

Problem 1. The unit distances problem

One may say that the main open problem involving geometric incidences is Erdös’s unit distances problem. To quote the book Research Problems in Discrete Geometry, this is

“possibly the best known (and simplest to explain) problem in combinatorial geometry”.

The problem simply asks: In a set of {n} points in {\mathbb{R}^2}, what is the maximum number of pairs of point at a distance of one? For example, {n} equally spaced points on a line span {n-1} unit distances. Using a lattice, one can obtain {n^{1+c/\log\log n}} unit distances, for some constant {c}. The current best upper bound states that every {n} points in the plane span {O(n^{4/3})} unit distances. Even though this is a central problem in Discrete Geometry, with many consequences, the last progress for it was obtained in the early 1980’s. The lower bound has not change since the 1940’s!

The unit distances problem is asymptotically equivalent to finding the maximum number of incidences between {n} points and {n} circles or radius one in {\mathbb{R}^2}. Indeed, consider a set of {n} points in {\mathbb{R}^2}. By placing a circle of radius one around every point, the number of point-circle incidences is twice the number of unit distances. One can move from the incidence problem to the unit distances problem in a similar manner.

Unitcircles

It turns out that the problem significantly changes for different norms:

  • As already stated, for the Euclidean distance norm (the {\ell_2}-norm) this is a long-standing difficult problem.
  • For the {\ell_1}– and {\ell_\infty}-norms, one can easily find {n} points that span {\Theta(n^2)} unit distances.
  • Valtr showed that there is a simply-defined norm for which the answer is {\Theta(n^{4/3})}.
  • Matoušek showed that for a generic norm the maximum number of unit distances is {O(n \log n \log \log n)}.

Note that the conjectured bound {n^{1+c/\log\log n}} for {\ell_2} is different from all of the bounds stated above. In particular, this bound is asymptotically larger than {n \log n \log \log n}. Thus, any solution for the unit distances problem must rely an a property that is almost unique to the Euclidean distance norm. One may say that this problem is about studying properties of the underlying geometry.

The distinct distances problem is another main problem of the field. Guth and Katz almost completely solved this problem, and their work is often considered as the field’s most significant progress in the past decade. One can think of the unit distances problem as more difficult, since a solution to unit distances implies a solution to distinct distances, up to sub-polynomial factors. (For Harmonic Analysis people, the distinct distances problem seemed to have been the more interesting one, due to its connections with the Kakeya conjecture).

Problem 2. Incidences with other algebraic curves in {\mathbb{R}^2}

We know the maximum number of incidences between {m} points and {n} lines in {\mathbb{R}^2}. But what happens when replacing the lines with {n} circles? Parabolas? Arbitrary polynomial curves of degree three? Unfortunately, all of these problems are wide open. If you would now arbitrarily choose another variant, it will most likely also be wide open. The only other cases that are resolved in {\mathbb{R}^2} are a few very specific 2-parameter families of curves. For example, the problem is solved for parabolas of the form {y=x^2+ax+b}, and also for circles incident to the origin.

One can come up with infinitely many incidence problems with algebraic curves in {\mathbb{R}^2}. So what are the main questions? The previous problem already discussed incidences with unit circles. The problem of incidences with arbitrary circles also has many applications. However, the following conjecture is probably considered to be more important than incidences with arbitrary circles.

When discussing a family of algebraic curves, we may consider the number of parameters necessary to define a member of the family. For example, an arbitrary circle can be defined as {(x-a)^2+(y-b)^2=r^2} for parameters {a,b,r}. That is, the set of circles in {\mathbb{R}^2} is a three-parameter family. Similarly, the parabolas defined as {y=ax^2+bx+c} also form a three-parameter family.

Conjecture 1. Let {P} be a set of {m} points and let {\Gamma} be a family of {n} constant-degre algebraic curves defined using {k} parameters, both in {\mathbb{R}^2}. If {n\le m}, then

\displaystyle  I(P,\Gamma)=O_k\left(m^{2/3}n^{2/3}+m+n\right).

It is known that the restriction {n\le m} in the conjecture is necessary. For examples, see this construction for circles and this construction for parabolas. At the moment, the conjecture is open for any family of algebraic curves defined using at least three parameters. The current best bound, by Sharir and Zahl, is stated in the following theorem.

Theorem 2 Let {P} be a set of {m} points and let {\Gamma} be a set of {n} constant-degree algebraic curves defined using at most {k} parameters, both in {\mathbb{R}^2}. Then for any {\varepsilon>0},

\displaystyle  I(P,\Gamma)=O_k\left(m^{\frac{2k}{5k-4}}n^{\frac{5k-6}{5k-4}+\varepsilon}+m^{2/3}n^{2/3}+m+n\right).

Unlike the conjecture, this bound strongly depends on {k}. Sometimes the conjecture is stated with {k} being the degree of the curves, instead of the number of parameters. This is not so different, since the set of algebraic curves of degree at most {k} is defined using {\binom{k+2}{2}} parameters. (Still, the two cases are not quite the same.)

That’s it for now. More problems will appear in the next post of this series.

Incidences in a Recent Work of Walsh

Recently, Miguel Walsh posted a very interesting paper on arXiv. The main purpose of the paper is to study various properties of polynomials and varieties. These properties are related to incidence problems – some originally arose from studying incidences. Walsh also presents new incidence bounds as applications of his results. In this post I’ll briefly discuss the incidence aspects of Walsh’s paper. Since this is a rather specialized post for incidence researchers, it assumes familiarity with the problems and notation.

walsh
Miguel Walsh

It seems to me that Walsh’s paper makes three main contributions to the study of incidence problems. The first two contributions are explicitly stated in the paper:

  • The paper derives a new polynomial partitioning theorem for points on a variety, with a good dependency on the degree of the variety. This was the missing step for removing an extra \varepsilon  in the exponent from most of the existing incidence bounds in {\mathbb R}^d  . For example, it should remove the extra \varepsilon  in the results of several of my papers, such as this one and that one.
  • As an application of his results, Walsh introduces an incidence problem that I did not see before. In this problem we study incidences between points and varieties in {\mathbb R}^d  , but the degrees of the varieties are not constant. That is, the degrees of the varieties are allowed to depend on the number of points and on the number of varieties. It would be interesting to see how this variant develops. For example, what applications in other subfields it might have.

The two above incidence results are definitely interesting, but I suspect that the paper would have a more significant effect on the incidence community in a different way. The paper makes significant progress in our understanding of polynomials and varieties, which directly affect the algebraic methods used to derive incidence bounds. This improved understanding could potentially be what we need to address some of the main problems that we have been trying to solve for a while. Me and other incidences researchers will definitely spend time reading the paper carefully, and think how it might fit with these problems. Walsh also mentions a follow-up paper, and I wonder if he has something similar in mind. I am planning to soon write a post about the current main open problems in incidence theory, and will then mention more clearly what I am referring to.

It might also be worth discussing the lower bounds part of the paper. The paper contains matching lower bounds for some of its incidence results. However, these lower bounds seem to apply specifically to the new variant of incidences with varieties of non-constant degrees. The “standard” problem of incidences with bounded-degree hypersurfaces in {\mathbb R}^d  remains open. In particular, we have matching lower bounds only in some cases. For an up-to-date discussion of the known lower bounds, see for example the relevant part in the introduction of my recent work with Thao Do.

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.

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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