Abstract

Let {U t N } t≥0 be a standard Brownian motion on 𝕌N. For fixed N∈ℕ and t>0, we give explicit almost-sure bounds on the L 1 -Wasserstein distance between the empirical spectral measure of U t N and the large-N limiting measure. The bounds obtained are tight enough that we are able to use them to study the evolution of the eigenvalue process in time, bounding the rate of convergence of paths of the measures on compact time intervals. The proofs use tools developed by the first author to obtain rates of convergence of the empirical spectral measures in classical random matrix ensembles, as well as recent estimates for the rates of convergence of moments of the ensemble-averaged spectral distribution.

Highlights

  • This paper studies the convergence of the empirical spectral measure of Brownian motion on the unitary group U (N ) to its large N limit

  • A significant focus in random matrix theory in recent years has been in obtaining non-asymptotic results; that is, quantitative results describing the behavior of random matrices of fixed size; see, for example, [RV10]

  • We combine some of these techniques with recent estimates on the rates of convergence of the moments for the empirical spectral distribution of unitary Brownian motion [CDK18] to prove asymptotically almost sure rates of convergence

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Summary

Introduction

This paper studies the convergence of the empirical spectral measure of Brownian motion on the unitary group U (N ) to its large N limit.

A concentration inequality for heat kernel measure
Concentration of μNt
Convergence to νt
Findings
Convergence of paths
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