Fourier Sparsity of GF(2) Polynomials

TL;DR

This paper investigates the relationship between the degree reduction of GF(2) polynomials and their Fourier sparsity, revealing that certain high-degree monomials imply large sparsity regardless of lower-degree terms.

Contribution

It introduces a new technique for proving lower bounds on Fourier sparsity and applies it to special classes of GF(2) polynomials, supporting the linear rank conjecture.

Findings

High-degree monomials imply large Fourier sparsity

New technique for lower bounds on Fourier sparsity

Supports the linear rank conjecture

Abstract

We study a conjecture called "linear rank conjecture" recently raised in (Tsang et al., FOCS'13), which asserts that if many linear constraints are required to lower the degree of a GF(2) polynomial, then the Fourier sparsity (i.e. number of non-zero Fourier coefficients) of the polynomial must be large. We notice that the conjecture implies a surprising phenomenon that if the highest degree monomials of a GF(2) polynomial satisfy a certain condition, then the Fourier sparsity of the polynomial is large regardless of the monomials of lower degrees -- whose number is generally much larger than that of the highest degree monomials. We develop a new technique for proving lower bound on the Fourier sparsity of GF(2) polynomials, and apply it to certain special classes of polynomials to showcase the above phenomenon.