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On the singularity of random symmetric matrices (1904.11478v2)

Published 25 Apr 2019 in math.CO and math.PR

Abstract: A well-known conjecture states that a random symmetric $n \times n$ matrix with entries in ${-1,1}$ is singular with probability $\Theta\big( n2 2{-n} \big)$. In this paper we prove that the probability of this event is at most $\exp\big( - \Omega( \sqrt{n} ) \big)$, improving the best known bound of $\exp\big( - \Omega( n{1/4} \sqrt{\log n} ) \big)$, which was obtained recently by Ferber and Jain. The main new ingredient is an inverse Littlewood-Offord theorem in $\mathbb{Z}_pn$ that applies under very mild conditions, whose statement is inspired by the method of hypergraph containers.

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