English

Hilbert Functions and Low-Degree Randomness Extractors

Computational Complexity 2024-05-17 v1

Abstract

For SFnS\subseteq \mathbb{F}^n, consider the linear space of restrictions of degree-dd polynomials to SS. The Hilbert function of SS, denoted hS(d,F)\mathrm{h}_S(d,\mathbb{F}), is the dimension of this space. We obtain a tight lower bound on the smallest value of the Hilbert function of subsets SS of arbitrary finite grids in Fn\mathbb{F}^n with a fixed size S|S|. We achieve this by proving that this value coincides with a combinatorial quantity, namely the smallest number of low Hamming weight points in a down-closed set of size S|S|. Understanding the smallest values of Hilbert functions is closely related to the study of degree-dd closure of sets, a notion introduced by Nie and Wang (Journal of Combinatorial Theory, Series A, 2015). We use bounds on the Hilbert function to obtain a tight bound on the size of degree-dd closures of subsets of Fqn\mathbb{F}_q^n, which answers a question posed by Doron, Ta-Shma, and Tell (Computational Complexity, 2022). We use the bounds on the Hilbert function and degree-dd closure of sets to prove that a random low-degree polynomial is an extractor for samplable randomness sources. Most notably, we prove the existence of low-degree extractors and dispersers for sources generated by constant-degree polynomials and polynomial-size circuits. Until recently, even the existence of arbitrary deterministic extractors for such sources was not known.

Keywords

Cite

@article{arxiv.2405.10277,
  title  = {Hilbert Functions and Low-Degree Randomness Extractors},
  author = {Alexander Golovnev and Zeyu Guo and Pooya Hatami and Satyajeet Nagargoje and Chao Yan},
  journal= {arXiv preprint arXiv:2405.10277},
  year   = {2024}
}
R2 v1 2026-06-28T16:29:50.719Z