On the Probabilistic Degrees of Symmetric Boolean functions

TL;DR

This paper characterizes the probabilistic degrees of all symmetric Boolean functions across all fields of fixed characteristic, providing key insights into their complexity and applications in computational theory.

Contribution

It offers a comprehensive characterization of probabilistic degrees of symmetric Boolean functions up to polylogarithmic factors over all fixed characteristic fields.

Findings

Probabilistic degrees of symmetric Boolean functions are characterized up to polylogarithmic factors.

Results apply uniformly across all fields of fixed characteristic.

Implications for lower bounds, pseudorandom generators, and algorithms in complexity theory.

Abstract

The probabilistic degree of a Boolean function $f:\{0,1\}^n\rightarrow \{0,1\}$ is defined to be the smallest $d$ such that there is a random polynomial $\mathbf{P}$ of degree at most $d$ that agrees with $f$ at each point with high probability. Introduced by Razborov (1987), upper and lower bounds on probabilistic degrees of Boolean functions --- specifically symmetric Boolean functions --- have been used to prove explicit lower bounds, design pseudorandom generators, and devise algorithms for combinatorial problems. In this paper, we characterize the probabilistic degrees of all symmetric Boolean functions up to polylogarithmic factors over all fields of fixed characteristic (positive or zero).