On the Local Semicircular Law for Wigner Ensembles

TL;DR

This paper proves a high-probability bound on the deviation of the empirical spectral distribution of Wigner matrices from the semicircular law, extending previous results and providing new proofs and applications.

Contribution

It extends recent results on the local semicircular law for Wigner matrices, offering sharper bounds, new proofs, and applications to eigenvalue rigidity and eigenvector delocalization.

Findings

High-probability bound of order (nv)^{-1} log n for spectral distribution deviation

Optimal delocalization of eigenvectors matching GOE ensembles

Shorter proof for O(n^{-1}) convergence rate of expected spectral distribution

Abstract

We consider a random symmetric matrix ${\bf X} = [X_{jk}]_{j,k=1}^n$ with upper triangular entries being i.i.d. random variables with mean zero and unit variance. We additionally suppose that $\mathbb E |X_{11}|^{4 + \delta} =: \mu_{4+\delta} < \infty$ for some $\delta > 0$. The aim of this paper is to significantly extend recent result of the authors [18] and show that with high probability the typical distance between the Stieltjes transform of the empirical spectral distribution (ESD) of the matrix $n^{-\frac{1}{2}} {\bf X}$ and Wigner's semicircle law is of order $(nv)^{-1} \log n$, where $v$ denotes the distance to the real line in the complex plane. We apply this result to the rate of convergence of the ESD to the distribution function of the semicircle law as well as to rigidity of eigenvalues and eigenvector delocalization significantly extending a recent result by G\"otze, Naumov and Tikhomirov [19]. The result on delocalization is optimal by comparison with GOE ensembles. Furthermore the techniques of this paper provide a new shorter proof for the optimal $O(n^{-1})$ rate of convergence of the expected ESD to the semicircle law.