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We introduce a new random matrix model called distance covariance matrix in this paper, whose normalized trace is equivalent to the distance covariance. We first derive a deterministic limit for the eigenvalue distribution of the distance…

Statistics Theory · Mathematics 2021-05-18 Weiming Li , Qinwen Wang , Jianfeng Yao

What is the connection of random matrices with integrable systems? Is this connection really useful? Introducing apprpriate times in the distribution of the ensemble of matrices, one shows that the corresponding distribution of the…

solv-int · Physics 2008-02-03 Pierre van Moerbeke

In this paper we study ensembles of random symmetric matrices $\X_n = {X_{ij}}_{i,j = 1}^n$ with dependent entries such that $\E X_{ij} = 0$, $\E X_{ij}^2 = \sigma_{ij}^2$, where $\sigma_{ij}$ may be different numbers. Assuming that the…

Probability · Mathematics 2013-03-19 F. Götze , A. Naumov , A. Tikhomirov

The statistical properties of the quantum chaotic spectra have been studied, so far, only up to the second order correlation effects. The numerical as well as the analytical evidence that random matrix theory can successfully model the…

Condensed Matter · Physics 2009-10-28 Pragya Shukla

We consider random matrices whose entries are f(<Xi,Xj>) or f(||Xi-Xj||^2) for iid vectors Xi in R^p with normalized distribution. Assuming that f is sufficiently smooth and the distribution of Xi's is sufficiently nice, El Karoui [17]…

Probability · Mathematics 2013-05-22 Yen Do , Van Vu

By studying the family of $p$-dimensional scale mixtures, this paper shows for the first time a non trivial example where the eigenvalue distribution of the corresponding sample covariance matrix {\em does not converge} to the celebrated…

Methodology · Statistics 2017-05-16 Weiming Li , Jianfeng Yao

We extend the so-called "single ring theorem"[1], also known as the Haagerup-Larsen theorem[2], by showing that in the limit when the size of the matrix goes to infinity a particular correlator between left and right eigenvectors of the…

Mathematical Physics · Physics 2017-02-09 Serban Belinschi , Maciej A. Nowak , Roland Speicher , Wojciech Tarnowski

Girko matrices have independent and identically distributed entries of mean zero and unit variance. In this note, we consider the random matrix model formed by the ratio of two independent Girko matrices, its entries are dependent and…

Probability · Mathematics 2026-03-19 Djalil Chafaï , David García-Zelada , Yuan Yuan Xu

We study the spectrum of a random multigraph with a degree sequence ${\bf D}_n=(D_i)_{i=1}^n$ and average degree $1 \ll \omega_n \ll n$, generated by the configuration model, and also the spectrum of the analogous random simple graph. We…

Probability · Mathematics 2020-05-15 Amir Dembo , Eyal Lubetzky , Yumeng Zhang

The limiting distribution of eigenvalues of N x N random matrices has many applications. One of the most studied ensembles are real symmetric matrices with independent entries iidrv; the limiting rescaled spectral measure (LRSM)…

Probability · Mathematics 2012-12-27 Olivia Beckwith , Victor Luo , Steven J. Miller , Karen Shen , Nicholas Triantafillou

Let $\mathbf X=(X_{jk})$ denote a $n\times p$ random matrix with entries $X_{jk}$, which are independent for $1\le j\le n, 1\le k\le p$. Let $n,p$ tend to infinity such that $\frac np=y+O(n^{-1})\in(0,1]$. For those values of $n,p$ we…

Probability · Mathematics 2014-12-22 F. Götze , A. N. Tikhomirov

Let $\mathbf X=(X_{jk})_{j,k=1}^n$ denote a Hermitian random matrix with entries $X_{jk}$, which are independent for $1\le j\le k\le n$. We consider the rate of convergence of the empirical spectral distribution function of the matrix…

Probability · Mathematics 2015-07-03 F. Götze , A. Tikhomirov

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

Patterned random matrices such as the reverse circulant, the symmetric circulant, the Toeplitz and the Hankel matrices and their almost sure limiting spectral distribution (LSD), have attracted much attention. Under the assumption that the…

Probability · Mathematics 2022-03-14 Arup Bose , Koushik Saha , Priyanka Sen

We examine the empirical distribution of the eigenvalues and the eigenvectors of adjacency matrices of sparse regular random graphs. We find that when the degree sequence of the graph slowly increases to infinity with the number of…

Probability · Mathematics 2012-10-15 Ioana Dumitriu , Soumik Pal

We provide a perturbative expansion for the empirical spectral distribution of a Hermitian matrix with large size perturbed by a random matrix with small operator norm whose entries in the eigenvector basis of the first one are independent…

Probability · Mathematics 2017-10-03 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

We study random normal matrix models whose eigenvalues tend to be distributed within a narrow "band" around the unit circle of width proportional to $\frac1n$, where $n$ is the size of matrices. For general radially symmetric potentials…

Probability · Mathematics 2021-12-22 Sung-Soo Byun , Seong-Mi Seo

We consider the adjacency matrices of sparse random graphs from the Chung-Lu model, where edges are added independently between the $N$ vertices with varying probabilities $p_{ij}$. The rank of the matrix $(p_{ij})$ is some fixed positive…

Probability · Mathematics 2015-09-14 Ben Adlam , Ziliang Che

We prove the convergence of the empirical spectral measure of Wishart matrices with size-dependent entries and characterize the limiting law by its moments. We apply our result to the cases where the entries are Bernoulli variables with…

Probability · Mathematics 2017-10-18 Nathan Noiry

We study the distribution of eigenvalues of almost-Hermitian random matrices associated with the classical Gaussian and Laguerre unitary ensembles. In the almost-Hermitian setting, which was pioneered by Fyodorov, Khoruzhenko and Sommers in…

Probability · Mathematics 2023-05-30 Yacin Ameur , Sung-Soo Byun
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