Extreme eigenvalues of Log-concave Ensemble

TL;DR

This paper investigates the extreme eigenvalues of log-concave random matrix ensembles, achieving near-optimal eigenvalue location precision and establishing Tracy-Widom and Gaussian laws under certain conditions.

Contribution

It advances the understanding of spectral rigidity and eigenvalue distributions for log-concave ensembles, including Tracy-Widom law derivation.

Findings

Spectral rigidity of the log-concave ensemble is established.

Tracy-Widom law for extreme eigenvalues is derived under an unconditional assumption.

Gaussian law for extreme eigenvalues with strong spikes is demonstrated.

Abstract

In this paper, we consider the log-concave ensemble of random matrices, a class of covariance-type matrices $XX^*$ with isotropic log-concave $X$-columns. A main example is the covariance estimator of the uniform measure on isotropic convex body. Non-asymptotic estimates and first order asymptotic limits for the extreme eigenvalues have been obtained in the literature. In this paper, with the recent advancements on log-concave measures \cite{chen, KL22}, we take a step further to locate the eigenvalues with a nearly optimal precision, namely, the spectral rigidity of this ensemble is derived. Based on the spectral rigidity and an additional ``unconditional" assumption, we further derive the Tracy-Widom law for the extreme eigenvalues of $XX^*$, and the Gaussian law for the extreme eigenvalues in case strong spikes are present.