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OP-7567Status unassessedCombinatorics

Polynomial method via tensorizing

Additive combinatorics and its applications · Historical workshop question

Editorial mapping of AIMPL source category: Combinatorics. http://aimpl.org/addcombapp/ Not an author-supplied MSC code.

Historical list · status unassessedAs of 2026-09-08Source & evidence ↓

Problem statement

Let r\mathbf{r} be either arankarank or prankprank. Let AA be a tensor, and IdId is the identity tensor on the same space as AA. Suppose r(A)<r(Id)\mathbf{r}(A)< \mathbf{r}(Id). Is it true that r(A⊗m)<r(Id)mcm\mathbf{r}(A^{\otimes m}) < \mathbf{r}(Id)^m c^m for some constant c<1c<1?

Lean 4

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Background

Question context

The purpose of this problem is to extend the current polynomial method techniques to handle 4APs and more complicated patterns. It's about suggesting a notion of tensor rank that tensorizes. Let F\mathbb{F} be a field and A∈Fn×⋯×nA\in \mathbb{F}^{n\times \cdots \times n} be a dd-dimensional tensor. We can think of AA as a multilinear polynomial f:(Fn)d→Ff:(\mathbb{F}^n)^d\rightarrow \mathbb{F} on variables X1,⋯ ,Xd∈FnX_1,\cdots,X_d \in \mathbb{F}^n where AA specifies the coefficients of the monomials. In the following we introduce several notions of rank. Let rank(A)rank(A) be the minimum number of rank-one tensors that sum up to AA. We need to specify the definition of a rank-one tensor. There are several definitions of a rank-1 tensor ff.

rankrank-1:

f(X1,⋯ ,Xd)=g1(X1)⋯gd(Xd)f(X_1,\cdots,X_d) = g_1(X_1)\cdots g_d(X_d)

where each gi:Fn→Fg_i:\mathbb{F}^n\rightarrow\mathbb{F} is linear

sranksrank-1: There is some i∈[d]i\in [d] so that

f(X1,⋯ ,Xd)=g(Xi)f′(X1,⋯ ,Xd)f(X_1,\cdots,X_d) = g(X_i)f'(X_1,\cdots,X_d)

where gg is linear and f′f' does not depend on XiX_i.

prankprank-1: There is a subset ϕ≠S⊂[d]\phi\neq S\subset[d] so that

f(X1,⋯ ,Xd)=g(Xi:i∈S)h(Xi:i∉S)f(X_1,\cdots,X_d) = g(X_i: i\in S) h(X_i: i\notin S)

Note that prank(⋅)≤srank(⋅)≤rank(⋅)prank(\cdot)\leq srank(\cdot)\leq rank(\cdot). We introduce another notion of rank (only for Fp\mathbb{F}_p, where pp is prime) called analytic rank. Let Bias(f)=EX1,⋯ ,Xdωf(X1,⋯ ,Xd)Bias (f) = \mathbb{E}_{X_1,\cdots,X_d} \omega^{f(X_1,\cdots,X_d)} where ω\omega is a ppth root of unity. Also note that Bias(f)∈[0,1]Bias(f)\in [0,1]. Define arank(f)=−log⁡Bias(f).arank(f) = -\log Bias(f). We have that arank(⋅)≤prank(⋅)arank(\cdot)\leq prank(\cdot).

Now, let's see how these notions of rank are used to solve, say the capset problem. The idea is that the identity tensor has high rank for all definitions of arank,srank,prankarank,srank,prank, but the capset tensor has low rank. The capset tensor is C∈F3n×n×nC\in \mathbb{F}_3^{n\times n \times n} where n=3kn= 3^k for some kk. Given x,y,z∈F3kx,y,z\in \mathbb{F}_3^k we have C(x,y,z)=0C(x,y,z)= 0 if x+y+z≠0x+y+z\neq 0 and is 1 otherwise. If S⊂F3kS\subset \mathbb{F}_3^k is APAP-free, then C∣SC_{|S} (CC restricted to the set SS) is identity.

Progress & source assessment

Historical workshop record. Current open/solved status has not been independently reassessed.

Status note in the source

This is known if r\mathbf{r} is chosen to be sranksrank. Also, this problem, if true, has several consequences such as exponential upper bounds on size of 4AP4AP-free sets. More generally, it would be great to find any useful notion of rank that tensorizes.

References
  1. [1]Additive combinatorics and its applications link

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