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Abdul Basit, Artem Chernikov, Sergei Starchenko, Chiu-Minh Tran and I have uploaded to the arXiv our paper Zarankiewicz’s problem for semilinear hypergraphs. This paper is in the spirit of a number of results in extremal graph theory in which the bounds for various graph-theoretic problems or results can be greatly improved if one makes some additional hypotheses regarding the structure of the graph, for instance by requiring that the graph be “definable” with respect to some theory with good model-theoretic properties.

A basic motivating example is the question of counting the number of incidences between points and lines (or between points and other geometric objects). Suppose one has ${n}$ points and ${n}$ lines in a space. How many incidences can there be between these points and lines? The utterly trivial bound is ${n^2}$, but by using the basic fact that two points determine a line (or two lines intersect in at most one point), a simple application of Cauchy-Schwarz improves this bound to ${n^{3/2}}$. In graph theoretic terms, the point is that the bipartite incidence graph between points and lines does not contain a copy of ${K_{2,2}}$ (there does not exist two points and two lines that are all incident to each other). Without any other further hypotheses, this bound is basically sharp: consider for instance the collection of ${p^2}$ points and ${p^2+p}$ lines in a finite plane ${{\bf F}_p^2}$, that has ${p^3+p^2}$ incidences (one can make the situation more symmetric by working with a projective plane rather than an affine plane). If however one considers lines in the real plane ${{\bf R}^2}$, the famous Szemerédi-Trotter theorem improves the incidence bound further from ${n^{3/2}}$ to ${O(n^{4/3})}$. Thus the incidence graph between real points and lines contains more structure than merely the absence of ${K_{2,2}}$.

More generally, bounding on the size of bipartite graphs (or multipartite hypergraphs) not containing a copy of some complete bipartite subgraph ${K_{k,k}}$ (or ${K_{k,\dots,k}}$ in the hypergraph case) is known as Zarankiewicz’s problem. We have results for all ${k}$ and all orders of hypergraph, but for sake of this post I will focus on the bipartite ${k=2}$ case.

In our paper we improve the ${n^{3/2}}$ bound to a near-linear bound in the case that the incidence graph is “semilinear”. A model case occurs when one considers incidences between points and axis-parallel rectangles in the plane. Now the ${K_{2,2}}$ condition is not automatic (it is of course possible for two distinct points to both lie in two distinct rectangles), so we impose this condition by fiat:

Theorem 1 Suppose one has ${n}$ points and ${n}$ axis-parallel rectangles in the plane, whose incidence graph contains no ${K_{2,2}}$‘s, for some large ${n}$.
• (i) The total number of incidences is ${O(n \log^4 n)}$.
• (ii) If all the rectangles are dyadic, the bound can be improved to ${O( n \frac{\log n}{\log\log n} )}$.
• (iii) The bound in (ii) is best possible (up to the choice of implied constant).

We don’t know whether the bound in (i) is similarly tight for non-dyadic boxes; the usual tricks for reducing the non-dyadic case to the dyadic case strangely fail to apply here. One can generalise to higher dimensions, replacing rectangles by polytopes with faces in some fixed finite set of orientations, at the cost of adding several more logarithmic factors; also, one can replace the reals by other ordered division rings, and replace polytopes by other sets of bounded “semilinear descriptive complexity”, e.g., unions of boundedly many polytopes, or which are cut out by boundedly many functions that enjoy coordinatewise monotonicity properties. For certain specific graphs we can remove the logarithmic factors entirely. We refer to the preprint for precise details.

The proof techniques are combinatorial. The proof of (i) relies primarily on the order structure of ${{\bf R}}$ to implement a “divide and conquer” strategy in which one can efficiently control incidences between ${n}$ points and rectangles by incidences between approximately ${n/2}$ points and boxes. For (ii) there is additional order-theoretic structure one can work with: first there is an easy pruning device to reduce to the case when no rectangle is completely contained inside another, and then one can impose the “tile partial order” in which one dyadic rectangle ${I \times J}$ is less than another ${I' \times J'}$ if ${I \subset I'}$ and ${J' \subset J}$. The point is that this order is “locally linear” in the sense that for any two dyadic rectangles ${R_-, R_+}$, the set ${[R_-,R_+] := \{ R: R_- \leq R \leq R_+\}}$ is linearly ordered, and this can be exploited by elementary double counting arguments to obtain a bound which eventually becomes ${O( n \frac{\log n}{\log\log n})}$ after optimising certain parameters in the argument. The proof also suggests how to construct the counterexample in (iii), which is achieved by an elementary iterative construction.

I’ve just uploaded to the arXiv the paper “Finite time blowup for an averaged three-dimensional Navier-Stokes equation“, submitted to J. Amer. Math. Soc.. The main purpose of this paper is to formalise the “supercriticality barrier” for the global regularity problem for the Navier-Stokes equation, which roughly speaking asserts that it is not possible to establish global regularity by any “abstract” approach which only uses upper bound function space estimates on the nonlinear part of the equation, combined with the energy identity. This is done by constructing a modification of the Navier-Stokes equations with a nonlinearity that obeys essentially all of the function space estimates that the true Navier-Stokes nonlinearity does, and which also obeys the energy identity, but for which one can construct solutions that blow up in finite time. Results of this type had been previously established by Montgomery-Smith, Gallagher-Paicu, and Li-Sinai for variants of the Navier-Stokes equation without the energy identity, and by Katz-Pavlovic and by Cheskidov for dyadic analogues of the Navier-Stokes equations in five and higher dimensions that obeyed the energy identity (see also the work of Plechac and Sverak and of Hou and Lei that also suggest blowup for other Navier-Stokes type models obeying the energy identity in five and higher dimensions), but to my knowledge this is the first blowup result for a Navier-Stokes type equation in three dimensions that also obeys the energy identity. Intriguingly, the method of proof in fact hints at a possible route to establishing blowup for the true Navier-Stokes equations, which I am now increasingly inclined to believe is the case (albeit for a very small set of initial data).

To state the results more precisely, recall that the Navier-Stokes equations can be written in the form

$\displaystyle \partial_t u + (u \cdot \nabla) u = \nu \Delta u + \nabla p$

for a divergence-free velocity field ${u}$ and a pressure field ${p}$, where ${\nu>0}$ is the viscosity, which we will normalise to be one. We will work in the non-periodic setting, so the spatial domain is ${{\bf R}^3}$, and for sake of exposition I will not discuss matters of regularity or decay of the solution (but we will always be working with strong notions of solution here rather than weak ones). Applying the Leray projection ${P}$ to divergence-free vector fields to this equation, we can eliminate the pressure, and obtain an evolution equation

$\displaystyle \partial_t u = \Delta u + B(u,u) \ \ \ \ \ (1)$

purely for the velocity field, where ${B}$ is a certain bilinear operator on divergence-free vector fields (specifically, ${B(u,v) = -\frac{1}{2} P( (u \cdot \nabla) v + (v \cdot \nabla) u)}$. The global regularity problem for Navier-Stokes is then equivalent to the global regularity problem for the evolution equation (1).

An important feature of the bilinear operator ${B}$ appearing in (1) is the cancellation law

$\displaystyle \langle B(u,u), u \rangle = 0$

(using the ${L^2}$ inner product on divergence-free vector fields), which leads in particular to the fundamental energy identity

$\displaystyle \frac{1}{2} \int_{{\bf R}^3} |u(T,x)|^2\ dx + \int_0^T \int_{{\bf R}^3} |\nabla u(t,x)|^2\ dx dt = \frac{1}{2} \int_{{\bf R}^3} |u(0,x)|^2\ dx.$

This identity (and its consequences) provide essentially the only known a priori bound on solutions to the Navier-Stokes equations from large data and arbitrary times. Unfortunately, as discussed in this previous post, the quantities controlled by the energy identity are supercritical with respect to scaling, which is the fundamental obstacle that has defeated all attempts to solve the global regularity problem for Navier-Stokes without any additional assumptions on the data or solution (e.g. perturbative hypotheses, or a priori control on a critical norm such as the ${L^\infty_t L^3_x}$ norm).

Our main result is then (slightly informally stated) as follows

Theorem 1 There exists an averaged version ${\tilde B}$ of the bilinear operator ${B}$, of the form

$\displaystyle \tilde B(u,v) := \int_\Omega m_{3,\omega}(D) Rot_{3,\omega}$

$\displaystyle B( m_{1,\omega}(D) Rot_{1,\omega} u, m_{2,\omega}(D) Rot_{2,\omega} v )\ d\mu(\omega)$

for some probability space ${(\Omega, \mu)}$, some spatial rotation operators ${Rot_{i,\omega}}$ for ${i=1,2,3}$, and some Fourier multipliers ${m_{i,\omega}}$ of order ${0}$, for which one still has the cancellation law

$\displaystyle \langle \tilde B(u,u), u \rangle = 0$

and for which the averaged Navier-Stokes equation

$\displaystyle \partial_t u = \Delta u + \tilde B(u,u) \ \ \ \ \ (2)$

admits solutions that blow up in finite time.

(There are some integrability conditions on the Fourier multipliers ${m_{i,\omega}}$ required in the above theorem in order for the conclusion to be non-trivial, but I am omitting them here for sake of exposition.)

Because spatial rotations and Fourier multipliers of order ${0}$ are bounded on most function spaces, ${\tilde B}$ automatically obeys almost all of the upper bound estimates that ${B}$ does. Thus, this theorem blocks any attempt to prove global regularity for the true Navier-Stokes equations which relies purely on the energy identity and on upper bound estimates for the nonlinearity; one must use some additional structure of the nonlinear operator ${B}$ which is not shared by an averaged version ${\tilde B}$. Such additional structure certainly exists – for instance, the Navier-Stokes equation has a vorticity formulation involving only differential operators rather than pseudodifferential ones, whereas a general equation of the form (2) does not. However, “abstract” approaches to global regularity generally do not exploit such structure, and thus cannot be used to affirmatively answer the Navier-Stokes problem.

It turns out that the particular averaged bilinear operator ${B}$ that we will use will be a finite linear combination of local cascade operators, which take the form

$\displaystyle C(u,v) := \sum_{n \in {\bf Z}} (1+\epsilon_0)^{5n/2} \langle u, \psi_{1,n} \rangle \langle v, \psi_{2,n} \rangle \psi_{3,n}$

where ${\epsilon_0>0}$ is a small parameter, ${\psi_1,\psi_2,\psi_3}$ are Schwartz vector fields whose Fourier transform is supported on an annulus, and ${\psi_{i,n}(x) := (1+\epsilon_0)^{3n/2} \psi_i( (1+\epsilon_0)^n x)}$ is an ${L^2}$-rescaled version of ${\psi_i}$ (basically a “wavelet” of wavelength about ${(1+\epsilon_0)^{-n}}$ centred at the origin). Such operators were essentially introduced by Katz and Pavlovic as dyadic models for ${B}$; they have the essentially the same scaling property as ${B}$ (except that one can only scale along powers of ${1+\epsilon_0}$, rather than over all positive reals), and in fact they can be expressed as an average of ${B}$ in the sense of the above theorem, as can be shown after a somewhat tedious amount of Fourier-analytic symbol manipulations.

If we consider nonlinearities ${\tilde B}$ which are a finite linear combination of local cascade operators, then the equation (2) more or less collapses to a system of ODE in certain “wavelet coefficients” of ${u}$. The precise ODE that shows up depends on what precise combination of local cascade operators one is using. Katz and Pavlovic essentially considered a single cascade operator together with its “adjoint” (needed to preserve the energy identity), and arrived (more or less) at the system of ODE

$\displaystyle \partial_t X_n = - (1+\epsilon_0)^{2n} X_n + (1+\epsilon_0)^{\frac{5}{2}(n-1)} X_{n-1}^2 - (1+\epsilon_0)^{\frac{5}{2} n} X_n X_{n+1} \ \ \ \ \ (3)$

where ${X_n: [0,T] \rightarrow {\bf R}}$ are scalar fields for each integer ${n}$. (Actually, Katz-Pavlovic worked with a technical variant of this particular equation, but the differences are not so important for this current discussion.) Note that the quadratic terms on the RHS carry a higher exponent of ${1+\epsilon_0}$ than the dissipation term; this reflects the supercritical nature of this evolution (the energy ${\frac{1}{2} \sum_n X_n^2}$ is monotone decreasing in this flow, so the natural size of ${X_n}$ given the control on the energy is ${O(1)}$). There is a slight technical issue with the dissipation if one wishes to embed (3) into an equation of the form (2), but it is minor and I will not discuss it further here.

In principle, if the ${X_n}$ mode has size comparable to ${1}$ at some time ${t_n}$, then energy should flow from ${X_n}$ to ${X_{n+1}}$ at a rate comparable to ${(1+\epsilon_0)^{\frac{5}{2} n}}$, so that by time ${t_{n+1} \approx t_n + (1+\epsilon_0)^{-\frac{5}{2} n}}$ or so, most of the energy of ${X_n}$ should have drained into the ${X_{n+1}}$ mode (with hardly any energy dissipated). Since the series ${\sum_{n \geq 1} (1+\epsilon_0)^{-\frac{5}{2} n}}$ is summable, this suggests finite time blowup for this ODE as the energy races ever more quickly to higher and higher modes. Such a scenario was indeed established by Katz and Pavlovic (and refined by Cheskidov) if the dissipation strength ${(1+\epsilon)^{2n}}$ was weakened somewhat (the exponent ${2}$ has to be lowered to be less than ${\frac{5}{3}}$). As mentioned above, this is enough to give a version of Theorem 1 in five and higher dimensions.

On the other hand, it was shown a few years ago by Barbato, Morandin, and Romito that (3) in fact admits global smooth solutions (at least in the dyadic case ${\epsilon_0=1}$, and assuming non-negative initial data). Roughly speaking, the problem is that as energy is being transferred from ${X_n}$ to ${X_{n+1}}$, energy is also simultaneously being transferred from ${X_{n+1}}$ to ${X_{n+2}}$, and as such the solution races off to higher modes a bit too prematurely, without absorbing all of the energy from lower modes. This weakens the strength of the blowup to the point where the moderately strong dissipation in (3) is enough to kill the high frequency cascade before a true singularity occurs. Because of this, the original Katz-Pavlovic model cannot quite be used to establish Theorem 1 in three dimensions. (Actually, the original Katz-Pavlovic model had some additional dispersive features which allowed for another proof of global smooth solutions, which is an unpublished result of Nazarov.)

To get around this, I had to “engineer” an ODE system with similar features to (3) (namely, a quadratic nonlinearity, a monotone total energy, and the indicated exponents of ${(1+\epsilon_0)}$ for both the dissipation term and the quadratic terms), but for which the cascade of energy from scale ${n}$ to scale ${n+1}$ was not interrupted by the cascade of energy from scale ${n+1}$ to scale ${n+2}$. To do this, I needed to insert a delay in the cascade process (so that after energy was dumped into scale ${n}$, it would take some time before the energy would start to transfer to scale ${n+1}$), but the process also needed to be abrupt (once the process of energy transfer started, it needed to conclude very quickly, before the delayed transfer for the next scale kicked in). It turned out that one could build a “quadratic circuit” out of some basic “quadratic gates” (analogous to how an electrical circuit could be built out of basic gates such as amplifiers or resistors) that achieved this task, leading to an ODE system essentially of the form

$\displaystyle \partial_t X_{1,n} = - (1+\epsilon_0)^{2n} X_{1,n}$

$\displaystyle + (1+\epsilon_0)^{5n/2} (- \epsilon^{-2} X_{3,n} X_{4,n} - \epsilon X_{1,n} X_{2,n} - \epsilon^2 \exp(-K^{10}) X_{1,n} X_{3,n}$

$\displaystyle + K X_{4,n-1}^2)$

$\displaystyle \partial_t X_{2,n} = - (1+\epsilon_0)^{2n} X_{2,n} + (1+\epsilon_0)^{5n/2} (\epsilon X_{1,n}^2 - \epsilon^{-1} K^{10} X_{3,n}^2)$

$\displaystyle \partial_t X_{3,n} = - (1+\epsilon_0)^{2n} X_{3,n} + (1+\epsilon_0)^{5n/2} (\epsilon^2 \exp(-K^{10}) X_{1,n}^2$

$\displaystyle + \epsilon^{-1} K^{10} X_{2,n} X_{3,n} )$

$\displaystyle \partial_t X_{4,n} =- (1+\epsilon_0)^{2n} X_{4,n} + (1+\epsilon_0)^{5n/2} (\epsilon^{-2} X_{3,n} X_{1,n}$

$\displaystyle - (1+\epsilon_0)^{5/2} K X_{4,n} X_{1,n+1})$

where ${K \geq 1}$ is a suitable large parameter and ${\epsilon > 0}$ is a suitable small parameter (much smaller than ${1/K}$). To visualise the dynamics of such a system, I found it useful to describe this system graphically by a “circuit diagram” that is analogous (but not identical) to the circuit diagrams arising in electrical engineering:

The coupling constants here range widely from being very large to very small; in practice, this makes the ${X_{2,n}}$ and ${X_{3,n}}$ modes absorb very little energy, but exert a sizeable influence on the remaining modes. If a lot of energy is suddenly dumped into ${X_{1,n}}$, what happens next is roughly as follows: for a moderate period of time, nothing much happens other than a trickle of energy into ${X_{2,n}}$, which in turn causes a rapid exponential growth of ${X_{3,n}}$ (from a very low base). After this delay, ${X_{3,n}}$ suddenly crosses a certain threshold, at which point it causes ${X_{1,n}}$ and ${X_{4,n}}$ to exchange energy back and forth with extreme speed. The energy from ${X_{4,n}}$ then rapidly drains into ${X_{1,n+1}}$, and the process begins again (with a slight loss in energy due to the dissipation). If one plots the total energy ${E_n := \frac{1}{2} ( X_{1,n}^2 + X_{2,n}^2 + X_{3,n}^2 + X_{4,n}^2 )}$ as a function of time, it looks schematically like this:

As in the previous heuristic discussion, the time between cascades from one frequency scale to the next decay exponentially, leading to blowup at some finite time ${T}$. (One could describe the dynamics here as being similar to the famous “lighting the beacons” scene in the Lord of the Rings movies, except that (a) as each beacon gets ignited, the previous one is extinguished, as per the energy identity; (b) the time between beacon lightings decrease exponentially; and (c) there is no soundtrack.)

There is a real (but remote) possibility that this sort of construction can be adapted to the true Navier-Stokes equations. The basic blowup mechanism in the averaged equation is that of a von Neumann machine, or more precisely a construct (built within the laws of the inviscid evolution ${\partial_t u = \tilde B(u,u)}$) that, after some time delay, manages to suddenly create a replica of itself at a finer scale (and to largely erase its original instantiation in the process). In principle, such a von Neumann machine could also be built out of the laws of the inviscid form of the Navier-Stokes equations (i.e. the Euler equations). In physical terms, one would have to build the machine purely out of an ideal fluid (i.e. an inviscid incompressible fluid). If one could somehow create enough “logic gates” out of ideal fluid, one could presumably build a sort of “fluid computer”, at which point the task of building a von Neumann machine appears to reduce to a software engineering exercise rather than a PDE problem (providing that the gates are suitably stable with respect to perturbations, but (as with actual computers) this can presumably be done by converting the analog signals of fluid mechanics into a more error-resistant digital form). The key thing missing in this program (in both senses of the word) to establish blowup for Navier-Stokes is to construct the logic gates within the laws of ideal fluids. (Compare with the situation for cellular automata such as Conway’s “Game of Life“, in which Turing complete computers, universal constructors, and replicators have all been built within the laws of that game.)

One of the oldest and most fundamental concepts in mathematics is the line. Depending on exactly what mathematical structures we want to study (algebraic, geometric, topological, order-theoretic, etc.), we model lines nowadays by a variety of standard mathematical objects, such as the real line ${\Bbb R}$, the complex line ${\Bbb C}$, the projective line $\Bbb{RP}^1$, the extended real line ${}[-\infty,+\infty]$, the affine line ${\Bbb A}^1$, the continuum $c$, the long line $L$, etc. We also have discrete versions of the line, such as the natural numbers ${\Bbb N}$, the integers ${\Bbb Z}$, and the ordinal $\omega$, as well as compact versions of the line, such as the unit interval ${}[0,1]$ or the unit circle ${\Bbb T} := {\Bbb R}/{\Bbb Z}$. Finally we have discrete and compact versions of the line, such as the cyclic groups ${\Bbb Z}/N{\Bbb Z}$ and the discrete intervals $\{1,\ldots,N\}$ and $\{0,\ldots,N-1\}$. By taking Cartesian products we then obtain higher-dimensional objects such as Euclidean space ${\Bbb R}^n$, the standard lattice ${\Bbb Z}^n$, the standard torus ${\Bbb T}^n = {\Bbb R}^n/{\Bbb Z}^n$, and so forth. These objects of course form the background on which a very large fraction of modern mathematics is set.

Broadly speaking, the line has three major families of structures on it:

1. Geometric structures, such as a metric or a measure, completeness, scales (coarse and fine), rigid motions (translations and reflection), similarities (dilation, affine maps), and differential structures (tangent bundle, etc.);
2. Algebraic structures, such group, ring, or field structures, and everything else that comes from those categories (e.g. subgroups, homomorphisms, involutions, etc.); and
3. One-dimensional structures, such as order, a length space structure (in particular, path-connectedness structure), a singleton generator, the Archimedean property, the ability to use mathematical induction (i.e. well-ordering), convexity, or the ability to disconnect the line by removing a single point.

Of course, these structures are inter-related, and it is an important phenomenon that a mathematical concept which appears to be native to one structure, can often be equivalently defined in terms of other structures. For instance, the absolute value $|n|$ of an integer $n$ can be defined geometrically as the distance from 0 to $n$, algebraically as the index of the subgroup $\langle n \rangle = n \cdot \Bbb Z$ of the integers ${\Bbb Z}$ generated by n, or one-dimensionally as the number of integers between 0 and $n$ (including 0, but excluding $n$). This equivalence of definitions becomes important when one wants to work in more general contexts in which one or more of the above structures is missing or otherwise weakened.

What I want to talk about today is an important toy model for the line (in any of its incarnations), in which the geometric and algebraic structures are enhanced (and become neatly nested and recursive), at the expense of the one-dimensional structure (which is largely destroyed). This model has many different names, depending on what field of mathematics one is working in and which structures one is interested in. In harmonic analysis it is called the dyadic model, the Walsh model, or the Cantor group model; in number theory and arithmetic geometry it is known as the function field model; in topology it is the Cantor space model; in probability it is the martingale model; in metric geometry it is the ultrametric, tree, or non-Archimedean model; in algebraic geometry it is the Puiseux series model; in additive combinatorics it is the bounded torsion or finite field model; in computer science and information theory it is the Hamming cube model; in representation theory it is the Kashiwara crystal model. Let me arbitrarily select one of these terms, and refer to all of these models as dyadic models for the line (or of objects derived from the line). While there is often no direct link between a dyadic model and a non-dyadic model, dyadic models serve as incredibly useful laboratories in which to gain insight and intuition for the “real-world” non-dyadic model, since one has much more powerful and elegant algebraic and geometric structure to play with in this setting (though the loss of one-dimensional structure can be a significant concern). Perhaps the most striking example of this is the three-line proof of the Riemann hypothesis in the function field model of the integers, which I will discuss a little later.