English

Random symmetric matrices: rank distribution and irreducibility of the characteristic polynomial

Probability 2021-06-09 v1 Number Theory

Abstract

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric {±1}\{\pm 1\}-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main innovation in our work is establishing sharp estimates regarding the rank distribution of symmetric random {±1}\{\pm 1\}-matrices over Fp\mathbb{F}_p for primes 2<pexp(O(n1/4))2 < p \leq \exp(O(n^{1/4})). Previously, such estimates were available only for p=o(n1/8)p = o(n^{1/8}). At the heart of our proof is a way to combine multiple inverse Littlewood--Offord-type results to control the contribution to singularity-type events of vectors in Fpn\mathbb{F}_p^{n} with anticoncentration at least 1/p+Ω(1/p2)1/p + \Omega(1/p^2). Previously, inverse Littlewood--Offord-type results only allowed control over vectors with anticoncentration at least C/pC/p for some large constant C>1C > 1.

Keywords

Cite

@article{arxiv.2106.04049,
  title  = {Random symmetric matrices: rank distribution and irreducibility of the characteristic polynomial},
  author = {Asaf Ferber and Vishesh Jain and Ashwin Sah and Mehtaab Sawhney},
  journal= {arXiv preprint arXiv:2106.04049},
  year   = {2021}
}

Comments

12 pages; comments welcome!