Stein's method, Markov processes, and linear eigenvalue statistics of random matrices

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Grzybowski, David, Meckes, Mark
Format: Preprint
Published: 2025
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866912615821737984
author Grzybowski, David
Meckes, Mark
author_facet Grzybowski, David
Meckes, Mark
contents We show how the infinitesimal exchangeable pairs approach to Stein's method combines naturally with the theory of Markov semigroups. We present a multivariate normal approximation theorem for functions of a random variable invariant with respect to a Markov semigroup. This theorem provides a Wasserstein distance bound in terms of quantities related to the infinitesimal generator of the semigroup. As an application, we deduce a rate of convergence for Johansson's celebrated theorem on linear eigenvalue statistics of Gaussian random matrix ensembles.
format Preprint
id arxiv_https___arxiv_org_abs_2509_25451
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Stein's method, Markov processes, and linear eigenvalue statistics of random matrices
Grzybowski, David
Meckes, Mark
Probability
We show how the infinitesimal exchangeable pairs approach to Stein's method combines naturally with the theory of Markov semigroups. We present a multivariate normal approximation theorem for functions of a random variable invariant with respect to a Markov semigroup. This theorem provides a Wasserstein distance bound in terms of quantities related to the infinitesimal generator of the semigroup. As an application, we deduce a rate of convergence for Johansson's celebrated theorem on linear eigenvalue statistics of Gaussian random matrix ensembles.
title Stein's method, Markov processes, and linear eigenvalue statistics of random matrices
topic Probability
url https://arxiv.org/abs/2509.25451