English

On the rank of a random symmetric matrix in the large deviation regime

Probability 2026-05-08 v2

Abstract

Let AA be an n×nn\times n random symmetric matrix with independent identically distributed subgaussian entries of unit variance. We prove the following large deviation inequality for the rank of AA: for all 1kcn1\leq k\leq c\sqrt{n}, P(Rank(A)nk)1exp(ckn),\mathbb{P}(\operatorname{Rank}(A)\geq n-k)\geq 1-\exp(-c'kn), for some fixed constants c,c>0c,c'>0. A similar large deviation inequality is proven for the rank of the adjacency matrix of dense Erdos-Renyi graphs. This corank estimate enhances the recent breakthrough of Campos, Jensen, Michelen and Sahasrabudhe that the singularity probability of a random symmetric matrix is exponentially small, and echoes a large deviation inequality of Mark Rudelson for the rank of a random matrix with independent entries.

Keywords

Cite

@article{arxiv.2506.01155,
  title  = {On the rank of a random symmetric matrix in the large deviation regime},
  author = {Yi Han},
  journal= {arXiv preprint arXiv:2506.01155},
  year   = {2026}
}

Comments

49 pages. To appear in JLMS