Concentration and convergence rates for spectral measures of random matrices

14Citations
Citations of this article
9Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

The topic of this paper is the typical behavior of the spectral measures of large random matrices drawn from several ensembles of interest, including in particular matrices drawn from Haar measure on the classical Lie groups, random compressions of random Hermitian matrices, and the so-called random sum of two independent random matrices. In each case, we estimate the expected Wasserstein distance from the empirical spectral measure to a deterministic reference measure, and prove a concentration result for that distance. As a consequence we obtain almost sure convergence of the empirical spectral measures in all cases. © 2012 Springer-Verlag.

Cite

CITATION STYLE

APA

Meckes, E. S., & Meckes, M. W. (2013). Concentration and convergence rates for spectral measures of random matrices. Probability Theory and Related Fields, 156(1–2), 145–164. https://doi.org/10.1007/s00440-012-0423-6

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free