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We compute explicit bounds in the normal and chi-square approximations of multilinear homogenous sums (of arbitrary order) of general centered independent random variables with unit variance. In particular, we show that chaotic random…

Probability · Mathematics 2010-11-08 Ivan Nourdin , Giovanni Peccati , Gesine Reinert

For general large non-Hermitian random matrices $X$ and deterministic normal deformations $A$, we prove that the local eigenvalue statistics of $A+X$ close to the critical edge points of its spectrum are universal. This concludes the proof…

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

We survey recent mathematical results about the spectrum of random band matrices. We start by exposing the Erd{\H o}s-Schlein-Yau dynamic approach, its application to Wigner matrices, and extension to other mean-field models. We then…

Probability · Mathematics 2018-08-31 Paul Bourgade

We consider real symmetric and complex Hermitian random matrices with the additional symmetry $h_{xy}=h_{N-x,N-y}$. The matrix elements are independent (up to the fourfold symmetry) and not necessarily identically distributed. This ensemble…

Mathematical Physics · Physics 2015-10-28 Johannes Alt

Universality, namely distributional invariance, is a well-known property for many random structures. For example, it is known to hold for a broad range of variational problems with random input. Much less is known about the algorithmic…

Data Structures and Algorithms · Computer Science 2025-12-25 Houssam El Cheairi , David Gamarnik

We consider the statistics of the extreme eigenvalues of sparse random matrices, a class of random matrices that includes the normalized adjacency matrices of the Erd{\H o}s-R{\'e}nyi graph $G(N,p)$. Recently, it was shown by Lee, up to an…

Probability · Mathematics 2023-05-05 Jiaoyang Huang , Horng-Tzer Yau

We consider the deformed Gaussian ensemble $H_n=H_n^{(0)}+M_n$ in which $H_n^{(0)}$ is a hermitian matrix (possibly random) and $M_n$ is the Gaussian unitary random matrix (GUE) independent of $H_n^{(0)}$. Assuming that the Normalized…

Mathematical Physics · Physics 2015-05-27 Tatyana Shcherbina

Parameter-dependent statistical properties of spectra of totally connected irregular quantum graphs with Neumann boundary conditions are studied. The autocorrelation functions of level velocities c(x) and c(w,x) as well as the distributions…

Chaotic Dynamics · Physics 2009-07-17 Oleh Hul , Petr Seba , Leszek Sirko

Orthogonal - unitary and symplectic - unitary crossover ensembles of random matrices are relevant in many contexts, especially in the study of time reversal symmetry breaking in quantum chaotic systems. Using skew-orthogonal polynomials we…

Mathematical Physics · Physics 2011-05-30 Santosh Kumar , Akhilesh Pandey

It is a classical result of Wigner that for an hermitian matrix with independent entries on and above the diagonal, the mean empirical eigenvalue distribution converges weakly to the semicircle law as matrix size tends to infinity. In this…

Probability · Mathematics 2007-07-17 Katrin Hofmann-Credner , Michael Stolz

An exchangeable random matrix is a random matrix with distribution invariant under any permutation of the entries. For such random matrices, we show, as the dimension tends to infinity, that the empirical spectral distribution tends to the…

Probability · Mathematics 2016-03-25 Radosław Adamczak , Djalil Chafaï , Paweł Wolff

We consider the random geometric graph on $n$ vertices drawn uniformly from a $d$--dimensional sphere. We focus on the sparse regime, when the expected degree is constant independent of $d$ and $n$. We show that, when $d$ is larger than $n$…

Probability · Mathematics 2021-10-22 Elliot Paquette , Andrew Vander Werf

We develop a unified approach to bounding the largest and smallest singular values of an inhomogeneous random rectangular matrix, based on the non-backtracking operator and the Ihara-Bass formula for general random Hermitian matrices with a…

Probability · Mathematics 2024-12-13 Ioana Dumitriu , Yizhe Zhu

We develop a new method for deriving local laws for a large class of random matrices. It is applicable to many matrix models built from sums and products of deterministic or independent random matrices. In particular, it may be used to…

Probability · Mathematics 2016-08-05 Antti Knowles , Jun Yin

We consider dynamically defined Hermitian matrices generated from orbits of the doubling map. We prove that their spectra fall into the GUE universality class from random matrix theory.

Probability · Mathematics 2022-01-05 Arka Adhikari , Marius Lemm

We consider the ensemble of adjacency matrices of Erd{\H o}s-R\'enyi random graphs, i.e.\ graphs on $N$ vertices where every edge is chosen independently and with probability $p \equiv p(N)$. We rescale the matrix so that its bulk…

Probability · Mathematics 2015-05-27 Laszlo Erdos , Antti Knowles , Horng-Tzer Yau , Jun Yin

In this paper, we study Dirac-type theorems for an inhomogenous random graph (G) whose edge probabilities are not necessarily all the same. We obtain sufficient conditions for the existence of Hamiltonian paths and perfect matchings, in…

Probability · Mathematics 2024-04-04 Ghurumuruhan Ganesan

The first paper in this series introduced a new family of nonasymptotic matrix concentration inequalities that sharply capture the spectral properties of very general random matrices in terms of an associated noncommutative model. These…

Probability · Mathematics 2025-11-13 Afonso S. Bandeira , Giorgio Cipolloni , Dominik Schröder , Ramon van Handel

In this paper, we prove a necessary and sufficient condition for the edge universality of sample covariance matrices with general population. We consider sample covariance matrices of the form $\mathcal Q = TX(TX)^{*}$, where the sample $X$…

Probability · Mathematics 2018-06-04 Xiucai Ding , Fan Yang

Products and sums of random matrices have seen a rapid development in the past decade due to various analytical techniques available. Two of these are the harmonic analysis approach and the concept of polynomial ensembles. Very recently, it…

Probability · Mathematics 2023-02-02 Mario Kieburg
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