English

Spectral radii of sparse random matrices

Probability 2021-01-25 v5

Abstract

We establish bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erd\H{o}s-R\'enyi graphs. Our error bounds are sharp for a large class of sparse random matrices. In particular, for the Erd\H{o}s-R\'enyi graph G(n,d/n)G(n,d/n), our results imply that the smallest and second-largest eigenvalues of the adjacency matrix converge to the edges of the support of the asymptotic eigenvalue distribution provided that dlognd \gg \log n. Together with the companion paper [3], where we analyse the extreme eigenvalues in the complementary regime dlognd \ll \log n, this establishes a crossover in the behaviour of the extreme eigenvalues around dlognd \sim \log n. Our results also apply to non-Hermitian sparse random matrices, corresponding to adjacency matrices of directed graphs. The proof combines (i) a new inequality between the spectral radius of a matrix and the spectral radius of its nonbacktracking version together with (ii) a new application of the method of moments for nonbacktracking matrices.

Keywords

Cite

@article{arxiv.1704.02945,
  title  = {Spectral radii of sparse random matrices},
  author = {Florent Benaych-Georges and Charles Bordenave and Antti Knowles},
  journal= {arXiv preprint arXiv:1704.02945},
  year   = {2021}
}
R2 v1 2026-06-22T19:13:06.048Z