scispace - formally typeset
Open AccessPosted Content

Lectures on the local semicircle law for Wigner matrices

TLDR
The local semicircle law of Wigner matrices has been studied in this paper, which states that the eigenvalue distribution of a random matrix with independent upper-triangular entries with zero expectation and constant variance is very similar to Wigners' distribution, down to spectral scales containing slightly more than one eigen value.
Abstract
These notes provide an introduction to the local semicircle law from random matrix theory, as well as some of its applications. We focus on Wigner matrices, Hermitian random matrices with independent upper-triangular entries with zero expectation and constant variance. We state and prove the local semicircle law, which says that the eigenvalue distribution of a Wigner matrix is close to Wigner's semicircle distribution, down to spectral scales containing slightly more than one eigenvalue. This local semicircle law is formulated using the Green function, whose individual entries are controlled by large deviation bounds. We then discuss three applications of the local semicircle law: first, complete delocalization of the eigenvectors, stating that with high probability the eigenvectors are approximately flat; second, rigidity of the eigenvalues, giving large deviation bounds on the locations of the individual eigenvalues; third, a comparison argument for the local eigenvalue statistics in the bulk spectrum, showing that the local eigenvalue statistics of two Wigner matrices coincide provided the first four moments of their entries coincide. We also sketch further applications to eigenvalues near the spectral edge, and to the distribution of eigenvectors.

read more

Citations
More filters
Posted Content

Cleaning large correlation matrices: tools from random matrix theory

TL;DR: In this article, a review of recent results concerning the estimation of large covariance matrices using tools from Random Matrix Theory (RMT) is presented, with an emphasis on the Marchenko-Pastur equation that provides information on the resolvent of multiplicatively corrupted noisy matrices.
Journal ArticleDOI

Kernel spectral clustering of large dimensional data

TL;DR: This article proposes a first analysis of kernel spectral clustering methods in the regime where the dimension of the data vectors to be clustered and their number of vectors grow large at the same rate, and evaluates precisely the position of these eigenvalues and the content of the eigenvectors.
Posted Content

Spectral radii of sparse random matrices

TL;DR: The paper establishes bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erdős-Renyi graphs and establishes a crossover in the behaviour of the extreme eigenvalues around $d \sim \log n$.
Posted Content

Random band matrices in the delocalized phase, I: Quantum unique ergodicity and universality

TL;DR: In this paper, Hou et al. showed that the eigenvalues locally converge to the point process given by the Gaussian orthogonal ensemble at any fixed energy in the bulk of the spectrum and in the large $N$ limit.
Journal ArticleDOI

Eigenvectors distribution and quantum unique ergodicity for deformed Wigner matrices

Lucas Benigni
- 19 Nov 2017 - 
TL;DR: In this paper, the distribution of eigenvectors for mesoscopic, mean-field perturbations of diagonal matrices in the bulk of the spectrum was analyzed for a generalized Rosenzweig-Porter model.
References
More filters
Book

Spectral Analysis of Large Dimensional Random Matrices

TL;DR: Wigner Matrices and Semicircular Law for Hadamard products have been used in this article for spectral separations and convergence rates of ESD for linear spectral statistics.
Journal ArticleDOI

On the Distribution of the Roots of Certain Symmetric Matrices

TL;DR: The distribution law obtained before' for a very special set of matrices is valid for much more general sets of real symmetric matrices of very high dimensionality.
Book

An Introduction to Random Matrices

TL;DR: The theory of random matrices plays an important role in many areas of pure mathematics and employs a variety of sophisticated mathematical tools (analytical, probabilistic and combinatorial) as mentioned in this paper.
Journal ArticleDOI

A Brownian‐Motion Model for the Eigenvalues of a Random Matrix

TL;DR: In this paper, a new type of Coulomb gas is defined, consisting of n point charges executing Brownian motions under the influence of their mutual electrostatic repulsions, and it is proved that this gas gives an exact mathematical description of the behavior of the eigenvalues of an (n × n) Hermitian matrix, when the elements of the matrix execute independent Brownian motion without mutual interaction.
Related Papers (5)