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We study the singularity probability of n*n random matrices with i.i.d. entries from highly biased discrete distributions. We obtain sharp non-asymptotic bounds for this probability and derive estimates on the least singular values. Our…

Probability · Mathematics 2025-12-12 Zeyan Song

We study the asymptotic behavior of the eigenvalues of Gaussian perturbations of large Hermitian random matrices for which the limiting eigenvalue density vanishes at a singular interior point or vanishes faster than a square root at a…

Probability · Mathematics 2019-03-27 Tom Claeys , Arno B. J. Kuijlaars , Karl Liechty , Dong Wang

We consider $N\times N$ Hermitian random matrices with independent identical distributed entries. The matrix is normalized so that the average spacing between consecutive eigenvalues is of order 1/N. Under suitable assumptions on the…

Mathematical Physics · Physics 2009-11-13 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau

We prove a local law in the bulk of the spectrum for random Gram matrices $XX^*$, a generalization of sample covariance matrices, where $X$ is a large matrix with independent, centered entries with arbitrary variances. The limiting…

Probability · Mathematics 2017-03-13 Johannes Alt , László Erdős , Torben Krüger

We establish bounds on the spectral radii for a large class of sparse random matrices, which includes the adjacency matrices of inhomogeneous Erd\H{o}s-R\'enyi graphs. Our error bounds are sharp for a large class of sparse random matrices.…

Probability · Mathematics 2021-01-25 Florent Benaych-Georges , Charles Bordenave , Antti Knowles

Random matrices whose entries come from a stationary Gaussian process are studied. The limiting behavior of the eigenvalues as the size of the matrix goes to infinity is the main subject of interest in this work. It is shown that the…

Probability · Mathematics 2016-04-22 Arijit Chakrabarty , Rajat Subhra Hazra , Deepayan Sarkar

We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

For general non-Hermitian random matrices $X$ and deterministic deformation matrices $A$, we prove that the local eigenvalue statistics of $A+X$ close to the typical edge points of its spectrum are universal. Furthermore, we show that under…

Probability · Mathematics 2025-07-14 Andrew Campbell , Giorgio Cipolloni , László Erdős , Hong Chang Ji

We present a generalization of the method of the local relaxation flow to establish the universality of local spectral statistics of a broad class of large random matrices. We show that the local distribution of the eigenvalues coincides…

Mathematical Physics · Physics 2010-08-20 Laszlo Erdos , Benjamin Schlein , Horng-Tzer Yau , Jun Yin

We consider real symmetric or complex hermitian random matrices with correlated entries. We prove local laws for the resolvent and universality of the local eigenvalue statistics in the bulk of the spectrum. The correlations have fast decay…

Probability · Mathematics 2018-03-01 Oskari Ajanki , Laszlo Erdos , Torben Krüger

In this paper we construct a class of random matrix ensembles labelled by a real parameter $\alpha \in (0,1)$, whose eigenvalue density near zero behaves like $|x|^\alpha$. The eigenvalue spacing near zero scales like $1/N^{1/(1+\alpha)}$…

High Energy Physics - Theory · Physics 2015-06-26 Romuald A. Janik

The diagonalization of matrices may be the top priority in the application of modern physics. In this paper, we numerically demonstrate that, for real symmetric random matrices with non-positive off-diagonal elements, a universal scaling…

Quantum Physics · Physics 2020-11-06 Wei Pan , Jing Wang , Deyan Sun

We investigate the eigenvalue density in ensembles of large sparse Bernoulli random matrices. We demonstrate that the fraction of linear subgraphs just below the percolation threshold is about 95\% of all finite subgraphs, and the…

Disordered Systems and Neural Networks · Physics 2016-01-20 V. Avetisov , P. L. Krapivsky , S. Nechaev

We study the sensitivity of the eigenvectors of random matrices, showing that even small perturbations make the eigenvectors almost orthogonal. More precisely, we consider two deformed Wigner matrices $W+D_1$, $W+D_2$ and show that their…

Probability · Mathematics 2026-03-03 Giorgio Cipolloni , László Erdős , Joscha Henheik , Oleksii Kolupaiev

Consider a $N\times n$ random matrix $Z_n=(Z^n_{j_1 j_2})$ where the individual entries are a realization of a properly rescaled stationary gaussian random field. The purpose of this article is to study the limiting empirical distribution…

Probability · Mathematics 2007-06-13 W. Hachem , P. Loubaton , J. Najim

Consider the normalized adjacency matrices of random $d$-regular graphs on $N$ vertices with fixed degree $d\geq3$. We prove that, with probability $1-N^{-1+{\varepsilon}}$ for any ${\varepsilon} >0$, the following two properties hold as $N…

Probability · Mathematics 2025-02-04 Jiaoyang Huang , Horng-Tzer Yau

Symmetric matrices with zero row sums occur in many theoretical settings and in real-life applications. When the offdiagonal elements of such matrices are i.i.d. random variables and the matrices are large, the eigenvalue distributions…

Disordered Systems and Neural Networks · Physics 2023-06-27 Pawat Akara-pipattana , Oleg Evnin

1. A standard Gaussian random matrix has full rank with probability 1 and is well-conditioned with a probability quite close to 1 and converging to 1 fast as the matrix deviates from square shape and becomes more rectangular. 2. If we…

Numerical Analysis · Mathematics 2016-03-17 Victor Y. Pan , Liang Zhao

Let $N(L)$ be the number of eigenvalues, in an interval of length $L$, of a matrix chosen at random from the Gaussian Orthogonal, Unitary or Symplectic ensembles of ${\cal N}$ by ${\cal N}$ matrices, in the limit ${\cal…

chao-dyn · Physics 2009-10-22 Ovidiu Costin , Joel L. Lebowitz

Let $\FF$ be an arbitrary field and $(\bm{G}_{n,d/n})_n$ be a sequence of sparse weighted Erd\H{o}s-R\'enyi random graphs on $n$ vertices with edge probability $d/n$, where weights from $\FF \setminus\{0\}$ are assigned to the edges…

Combinatorics · Mathematics 2023-01-31 Remco van der Hofstad , Noela Müller , Haodong Zhu