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Wegner estimate and upper bound on the eigenvalue condition number of non‐Hermitian random matrices.

Authors :
Erdős, László
Ji, Hong Chang
Source :
Communications on Pure & Applied Mathematics. Sep2024, Vol. 77 Issue 9, p3785-3840. 56p.
Publication Year :
2024

Abstract

We consider N×N$N\times N$ non‐Hermitian random matrices of the form X+A$X+A$, where A$A$ is a general deterministic matrix and NX$\sqrt {N}X$ consists of independent entries with zero mean, unit variance, and bounded densities. For this ensemble, we prove (i) a Wegner estimate, that is, that the local density of eigenvalues is bounded by N1+o(1)$N^{1+o(1)}$ and (ii) that the expected condition number of any bulk eigenvalue is bounded by N1+o(1)$N^{1+o(1)}$; both results are optimal up to the factor No(1)$N^{o(1)}$. The latter result complements the very recent matching lower bound obtained by Cipolloni et al. and improves the N$N$‐dependence of the upper bounds by Banks et al. and Jain et al. Our main ingredient, a near‐optimal lower tail estimate for the small singular values of X+A−z$X+A-z$, is of independent interest. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00103640
Volume :
77
Issue :
9
Database :
Academic Search Index
Journal :
Communications on Pure & Applied Mathematics
Publication Type :
Academic Journal
Accession number :
178355545
Full Text :
https://doi.org/10.1002/cpa.22201