An almost-tight $L^2$ autoconvolution inequality
Combinatorics
2022-11-01 v1 Number Theory
Abstract
Let denote the set of functions such that . We determine the value of up to a 0.0014\% error, thereby making progress on a problem asked by Ben Green. Furthermore, we prove that a unique minimizer exists. As a corollary, we obtain improvements on the maximum size of sets for .
Cite
@article{arxiv.2210.16437,
title = {An almost-tight $L^2$ autoconvolution inequality},
author = {Ethan Patrick White},
journal= {arXiv preprint arXiv:2210.16437},
year = {2022}
}
Comments
18 pages, 1 figure, 1 table