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Let $\log^{2+\varepsilon} n \le d \le n/2$ for some fixed $\varepsilon \in (0,1)$, and let $M_n$ be an $n\times n$ random matrix with entries in ${0,1}$, where each row is independently and uniformly sampled from the set of all vectors in…

Probability · Mathematics 2026-04-14 Dongbin Li , Alexander E. Litvak , Tingzhou Yu

Here we introduce the non-Hermitian diluted banded random matrix (nHdBRM) ensemble as the set of $N\times N$ real non-symmetric matrices whose entries are independent Gaussian random variables with zero mean and variance one if $|i-j|<b$…

Disordered Systems and Neural Networks · Physics 2024-06-25 M. Hernández-Sánchez , G. Tapia-Labra , J. A. Mendez-Bermudez

Let $X$ be a matrix sampled uniformly from the set of doubly stochastic matrices of size $n\times n$. We show that the empirical spectral distribution of the normalized matrix $\sqrt{n}(X-{\mathbf {E}}X)$ converges almost surely to the…

Combinatorics · Mathematics 2014-03-28 Hoi H. Nguyen

We discuss the limiting spectral density of real symmetric random matrices. Other than in standard random matrix theory the upper diagonal entries are not assumed to be independent, but we will fill them with the entries of a stochastic…

Probability · Mathematics 2015-12-09 Matthias Löwe , Kristina Schubert

The universality phenomenon asserts that the distribution of the eigenvalues of random matrix with i.i.d. zero mean, unit variance entries does not depend on the underlying structure of the random entries. For example, a plot of the…

Probability · Mathematics 2012-10-11 Philip Matchett Wood

We prove the universality for the eigenvalue gap statistics in the bulk of the spectrum for band matrices, in the regime where the band width is comparable with the dimension of the matrix, $W\sim N$. All previous results concerning…

Probability · Mathematics 2016-04-18 Paul Bourgade , Laszlo Erdos , Horng-Tzer Yau , Jun Yin

For a class of sparse random matrices of the form $A_n =(\xi_{i,j}\delta_{i,j})_{i,j=1}^n$, where $\{\xi_{i,j}\}$ are i.i.d.~centered sub-Gaussian random variables of unit variance, and $\{\delta_{i,j}\}$ are i.i.d.~Bernoulli random…

Probability · Mathematics 2018-06-13 Anirban Basak , Mark Rudelson

Disordered mechanical systems with high connectivity represent a limit opposite to the more familiar case of disordered crystals. Individual ions in a crystal are subjected essentially to nearest-neighbor interactions. In contrast, the…

Mathematical Physics · Physics 2022-02-01 Joshua Feinberg , Roman Riser

Consider a square random matrix with independent and identically distributed entries of mean zero and unit variance. We show that as the dimension tends to infinity, the spectral radius is equivalent to the square root of the dimension in…

Probability · Mathematics 2022-04-20 Charles Bordenave , Djalil Chafaï , David García-Zelada

We consider $N\times N$ Hermitian random band matrices $H=(H_{xy})$, whose entries are centered complex Gaussian random variables. The indices $x,y$ range over the $d$-dimensional discrete torus $(\mathbb Z/L\mathbb Z)^d$ with $d\in…

Probability · Mathematics 2025-06-25 Fan Yang , Jun Yin

Given an $n\times n$ random matrix $X_n$ with i.i.d. entries of unit variance, the circular law says that the empirical spectral distribution (ESD) of $X_n/\sqrt{n}$ converges to the uniform measure on the unit disk. Let $M_n$ be a…

Operator Algebras · Mathematics 2025-08-26 Ping Zhong

We consider non-Hermitian random matrices $X \in \mathbb{C}^{n \times n}$ with general decaying correlations between their entries. For large $n$, the empirical spectral distribution is well approximated by a deterministic density,…

Probability · Mathematics 2021-02-25 Johannes Alt , Torben Krüger

In the first part of this article, we proved a local version of the circular law up to the finest scale $N^{-1/2+ \e}$ for non-Hermitian random matrices at any point $z \in \C$ with $||z| - 1| > c $ for any $c>0$ independent of the size of…

Probability · Mathematics 2013-12-05 Paul Bourgade , Horng-Tzer Yau , Jun Yin

In this work we study symmetric random matrices with variance profile satisfying certain conditions. We establish the convergence of the operator norm of these matrices to the largest element of the support of the limiting empirical…

Probability · Mathematics 2024-04-23 Dimitris Cheliotis , Michail Louvaris

A large i.i.d. random matrix with deterministic low-rank perturbation has been extensively studied, particularly in the aspects of the ESD (Empirical Spectral Distribution) and the outliers of eigenvalues. In this work, we investigate the…

Information Theory · Computer Science 2025-06-24 Kun Chen , Zhihua Zhang

We prove that the local eigenvalue statistics for $d=1$ random band matrices with fixed bandwidth and, for example, Gaussian entries, is given by a Poisson point process and we identify the intensity of the process. The proof relies on an…

Mathematical Physics · Physics 2020-09-01 Benjamin Brodie , Peter D. Hislop

Let $\log^Cn\le d\le n/2$ for a sufficiently large constant $C>0$ and let $A_n$ denote the adjacency matrix of a uniform random $d$-regular directed graph on $n$ vertices. We prove that as $n$ tends to infinity, the empirical spectral…

Probability · Mathematics 2017-08-09 Nicholas A. Cook

We consider random $n\times n$ matrices $X$ with independent and centered entries and a general variance profile. We show that the spectral radius of $X$ converges with very high probability to the square root of the spectral radius of the…

Probability · Mathematics 2022-09-29 Johannes Alt , Laszlo Erdos , Torben Krüger

For each $n$, let $A_n=(\sigma_{ij})$ be an $n\times n$ deterministic matrix and let $X_n=(X_{ij})$ be an $n\times n$ random matrix with i.i.d. centered entries of unit variance. We study the asymptotic behavior of the empirical spectral…

Probability · Mathematics 2020-08-03 Nicholas A. Cook , Walid Hachem , Jamal Najim , David Renfrew

We analyze the asymptotic fluctuations of linear eigenvalue statistics of random centrosymmetric matrices with i.i.d. entries. We prove that for a complex analytic test function, the centered and normalized linear eigenvalue statistics of…

Probability · Mathematics 2025-10-20 Indrajit Jana , Sunita Rani