Singularity of discrete random matrices
Vishesh Jain, Ashwin Sah, Mehtaab Sawhney

TL;DR
This paper precisely determines the probability that a random matrix with discrete entries is singular, confirming a folklore conjecture and providing new asymptotic formulas for Bernoulli and uniform distributions.
Contribution
It confirms a folklore conjecture on the singularity probability of discrete random matrices and derives precise asymptotics for Bernoulli and uniform cases.
Findings
Exact asymptotics for Bernoulli(p) matrices with p<1/2
Improved bounds for Bernoulli(p) with p>1/2
Sharp analysis of the smallest singular value for uniform distributions
Abstract
Let be a non-constant real-valued random variable with finite support, and let denote an random matrix with entries that are independent copies of . For which is not uniform on its support, we show that \begin{align*} \mathbb{P}[M_{n}(\xi)\text{ is singular}] &= \mathbb{P}[\text{zero row or column}] + (1+o_n(1))\mathbb{P}[\text{two equal (up to sign) rows or columns}], \end{align*} thereby confirming a folklore conjecture. As special cases, we obtain: (1) For with fixed , \[\mathbb{P}[M_{n}(\xi)\text{ is singular}] = 2n(1-p)^{n} + (1+o_n(1))n(n-1)(p^2 + (1-p)^2)^{n},\] which determines the singularity probability to two asymptotic terms. Previously, no result of such precision was available in the study of the singularity of random matrices. (2) For with fixed $p \in…
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