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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 show that the global fluctuations of spectra of GOE and GUE matrices and their principal submatrices executing Dyson's Brownian motion are Gaussian in the limit of large matrix dimensions. For nested submatrices one obtains a limiting…

Probability · Mathematics 2010-11-17 Alexei Borodin

We prove eigenvalue processes from dynamical random matrix theory including Dyson Brownian motion, Wishart process, and Dynkin's Brownian motion of ellipsoids are results of projecting Brownian motion through Riemannian submersions induced…

Probability · Mathematics 2023-05-23 Ching-Peng Huang

We study the fluctuations of eigenvalues from a class of Wigner random matrices that generalize the Gaussian orthogonal ensemble. We begin by considering an $n \times n$ matrix from the Gaussian orthogonal ensemble (GOE) or Gaussian…

Probability · Mathematics 2011-03-03 Sean O'Rourke

Consider an $n\times n$ Hermitean matrix valued stochastic process $\{H_t\}_{t\geq 0}$ where the matrix elements evolve according to Ornstein-Uhlenbeck processes. It is well known that the eigenvalues perform a so called Dyson Brownian…

Probability · Mathematics 2012-04-16 Mark Adler , Eric Nordenstam , Pierre van Moerbeke

We define a new diffusive matrix model converging towards the $\beta$-Dyson Brownian motion for all $\beta\in [0,2]$ that provides an explicit construction of $\beta$-ensembles of random matrices that is invariant under the…

Probability · Mathematics 2013-06-25 Romain Allez , Alice Guionnet

Consider a high-dimensional Wishart matrix $\bd{W}=\bd{X}^T\bd{X}$ where the entries of $\bd{X}$ are i.i.d. random variables with mean zero, variance one, and a finite fourth moment $\eta$. Motivated by problems in signal processing and…

Probability · Mathematics 2024-10-22 Tiefeng Jiang , Yongcheng Qi

We study joint eigenvector distributions for large symmetric matrices in the presence of weak noise. Our main result asserts that every submatrix in the orthogonal matrix of eigenvectors converges to a multidimensional Gaussian…

Probability · Mathematics 2020-05-19 Jake Marcinek , Horng-Tzer Yau

The aim of this paper is to give a precise asymptotic description of some eigenvalue statistics stemming from random matrix theory. More precisely, we consider random determinants of the GUE, Laguerre, Uniform Gram and Jacobi beta ensembles…

Probability · Mathematics 2017-07-25 Martina Dal Borgo , Emma Hovhannisyan , Alain Rouault

We prove that any finite collection of quadratic forms (overlaps) of general deterministic matrices and eigenvectors of an $N\times N$ Wigner matrix has joint Gaussian fluctuations. This can be viewed as the random matrix analogue of the…

Probability · Mathematics 2022-12-22 Lucas Benigni , Giorgio Cipolloni

We study the mean diagonal overlap of left and right eigenvectors associated with complex eigenvalues in $N\times N$ non-Hermitian random Gaussian matrices. In well known works by Chalker and Mehlig the expectation of this (self-)overlap…

Mathematical Physics · Physics 2024-03-22 Mark J. Crumpton , Yan V. Fyodorov , Tim R. Würfel

We consider the random matrix ensemble with an external source \[ \frac{1}{Z_n} e^{-n \Tr({1/2}M^2 -AM)} dM \] defined on $n\times n$ Hermitian matrices, where $A$ is a diagonal matrix with only two eigenvalues $\pm a$ of equal…

Mathematical Physics · Physics 2009-11-10 Pavel M. Bleher , Arno B. J. Kuijlaars

We show that correlation matrices with particular average and variance of the correlation coefficients have a notably restricted spectral structure. Applying geometric methods, we derive lower bounds for the largest eigenvalue and the…

Mathematical Physics · Physics 2021-08-25 Yuriy Stepanov , Hendrik Herrmann , Thomas Guhr

The objective of this paper is to understand the superlinear convergence behavior of the GMRES method when the coefficient matrix has clustered eigenvalues. In order to understand the phenomenon, we analyze the convergence using the…

Numerical Analysis · Mathematics 2025-04-25 Zeyu Liao , Ken Hayami

This paper is the second chapter of three of the author's undergraduate thesis. In this paper, we consider the random matrix ensemble given by $(d_b, d_w)$-regular graphs on $M$ black vertices and $N$ white vertices, where $d_b \in…

Probability · Mathematics 2018-01-18 Kevin Yang

Recent applications in queuing theory and statistical mechanics have isolated the process formed by the eigenvalues of successive minors of the GUE. Analogous eigenvalue processes, formed in general from the eigenvalues of nested sequences…

Mathematical Physics · Physics 2015-06-16 Peter J. Forrester , Taro Nagao

We consider large non-Hermitian $N\times N$ matrices with an additive independent, identically distributed (i.i.d.) noise for each matrix elements. We show that already a small noise of variance $1/N$ completely thermalises the bulk…

Probability · Mathematics 2024-01-12 Giorgio Cipolloni , László Erdős , Joscha Henheik , Dominik Schröder

We establish the first quantitative Berry-Esseen bounds for edge eigenvector statistics in random regular graphs. For any $d$-regular graph on $N$ vertices with fixed $d \geq 3$ and deterministic unit vector $\mathbf{q} \perp \mathbf{e}$,…

Probability · Mathematics 2025-07-18 Leonhard Nagel

We study the angles between the eigenvectors of a random $n\times n$ complex matrix $M$ with density $\propto \mathrm{e}^{-n\operatorname{Tr}V(M^*M)}$ and $x\mapsto V(x^2)$ convex. We prove that for unit eigenvectors…

Probability · Mathematics 2018-09-27 Florent Benaych-Georges , Ofer Zeitouni

We consider eigenvectors of the Hamiltonian $H_0$ perturbed by a generic perturbation $V$ modelled by a random matrix from the Gaussian Unitary Ensemble (GUE). Using the supersymmetry approach we derive analytical results for the statistics…

Disordered Systems and Neural Networks · Physics 2017-01-04 Kevin Truong , Alexander Ossipov