Gaussian width bounds with applications to arithmetic progressions in random settings
Jop Bri\"et, Sivakanth Gopi

TL;DR
This paper establishes upper bounds on the Gaussian width of certain polynomial images of the Boolean hypercube and applies these bounds to problems in arithmetic progressions within random sets, improving existing probabilistic bounds.
Contribution
It introduces new Gaussian width bounds for polynomial images of hypercubes and applies them to enhance results on arithmetic progressions in random sets and large deviations.
Findings
Proves that random subsets are -intersective with high probability under improved probability bounds.
Provides quadratic improvements in large deviation estimates for the number of arithmetic progressions.
Connects bounds to error correcting codes and Banach space theory.
Abstract
Motivated by problems on random differences in Szemer\'{e}di's theorem and on large deviations for arithmetic progressions in random sets, we prove upper bounds on the Gaussian width of point sets that are formed by the image of the -dimensional Boolean hypercube under a mapping , where each coordinate is a constant-degree multilinear polynomial with 0-1 coefficients. We show the following applications of our bounds. Let be the random subset of containing each element independently with probability . A set is -intersective if any dense subset of contains a proper -term arithmetic progression with common difference in . Our main result implies that is -intersective with…
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