Asymptotic $L^4$ norm of polynomials derived from characters

TL;DR

This paper introduces new multivariable Littlewood polynomials with lower asymptotic $L^4$ to $L^2$ norm ratios than previously known, achieved through a comprehensive survey of polynomials derived from finite field characters.

Contribution

It is the first to find multivariable Littlewood polynomials with asymptotic norm ratios lower than any previously known, using a broad survey approach.

Findings

Discovered multivariable Littlewood polynomials with minimal asymptotic norm ratios.

Established that these polynomials outperform product-based constructions of univariate polynomials.

Provided new bounds for autocorrelation properties of multivariable polynomials.

Abstract

Littlewood investigated polynomials with coefficients in $\{-1,1\}$ (Littlewood polynomials), to see how small their ratio of norms $||f||_4/||f||_2$ on the unit circle can become as $deg(f)\to\infty$. A small limit is equivalent to slow growth in the mean square autocorrelation of the associated binary sequences of coefficients of the polynomials. The autocorrelation problem for arrays and higher dimensional objects has also been studied; it is the natural generalization to multivariable polynomials. Here we find, for each $n > 1$, a family of $n$-variable Littlewood polynomials with lower asymptotic $||f||_4/||f||_2$ than any known hitherto. We discover these through a wide survey, infeasible with previous methods, of polynomials whose coefficients come from finite field characters. This is the first time that the lowest known asymptotic ratio of norms $||f||_4/||f||_2$ for multivariable polynomials $f(z_1,...,z_n)$ is strictly less than what could be obtained by using products $f_1(z_1)... f_n(z_n)$ of the best known univariate polynomials.