Hilbert Functions and Low-Degree Randomness Extractors
Alexander Golovnev, Zeyu Guo, Pooya Hatami, Satyajeet, Nagargoje, Chao Yan

TL;DR
This paper establishes tight bounds on Hilbert functions of subsets in finite fields, linking algebraic and combinatorial properties, and applies these results to construct low-degree polynomial extractors for various randomness sources.
Contribution
It provides the first tight bounds on Hilbert functions for arbitrary finite grids and uses these to develop low-degree extractors for complex randomness sources.
Findings
Tight lower bounds on Hilbert functions for subsets of finite grids.
Bound on degree-d closures of subsets in finite fields.
Existence of low-degree polynomial extractors for sources generated by circuits.
Abstract
For , consider the linear space of restrictions of degree- polynomials to . The Hilbert function of , denoted , is the dimension of this space. We obtain a tight lower bound on the smallest value of the Hilbert function of subsets of arbitrary finite grids in with a fixed size . 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 . Understanding the smallest values of Hilbert functions is closely related to the study of degree- 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- closures of subsets of , which answers a…
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Taxonomy
TopicsNeural Networks and Applications · Computability, Logic, AI Algorithms
