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We prove that few largest (and most important) eigenvalues of random symmetric matrices of various kinds are very strongly concentrated. This strong concentration enables us to compute the means of these eigenvalues with high precision. Our…

Mathematical Physics · Physics 2007-05-23 Michael Krivelevich , Van H. Vu

We discuss an application of the random matrix theory in the context of estimating the bipartite entanglement of a quantum system. We discuss how the Wishart ensemble (the earliest studied random matrix ensemble) appears in this quantum…

Statistical Mechanics · Physics 2010-05-26 Satya N. Majumdar

We find uniform asymptotic formulas for all the eigenvalues of certain 7-diagonal symmetric Toeplitz matrices of large dimension. The entries of the matrices are real and we consider the case where the real-valued generating function such…

Spectral Theory · Mathematics 2021-11-16 V. Stukopin , S. Grudsky , I. Voronin , M. Barrera

This paper is devoted to a dispersion analysis of a class of perturbed p-Laplacians. Besides the p-Laplacian-like eigenvalue problems we also deal with new and non-standard eigenvalue problems, which can not be solved by the methods used in…

Spectral Theory · Mathematics 2010-10-21 Mahir Hasanov

We derive exact analytic expressions for the distributions of eigenvalues and singular values for the product of an arbitrary number of independent rectangular Gaussian random matrices in the limit of large matrix dimensions. We show that…

Statistical Mechanics · Physics 2013-05-29 Z. Burda , A. Jarosz , G. Livan , M. A. Nowak , A. Swiech

Two-term asymptotic formulae for the probability distribution functions for the smallest eigenvalue of the Jacobi $ \beta $-Ensembles are derived for matrices of large size in the r\'egime where $ \beta > 0 $ is arbitrary and one of the…

Probability · Mathematics 2024-01-24 B. Winn

We consider matrices formed by a random $N\times N$ matrix drawn from the Gaussian Orthogonal Ensemble (or Gaussian Unitary Ensemble) plus a rank-one perturbation of strength $\theta$, and focus on the largest eigenvalue, $x$, and the…

Probability · Mathematics 2019-04-04 Giulio Biroli , Alice Guionnet

Orthogonal polynomials and multiple orthogonal polynomials are interesting special functions because there is a beautiful theory for them, with many examples and useful applications in mathematical physics, numerical analysis, statistics…

Classical Analysis and ODEs · Mathematics 2020-07-14 Walter Van Assche

The logarithm of the diagonal matrix element of a high power of a random matrix converges to the Cole-Hopf solution of the Kardar-Parisi-Zhang equation in the sense of one-point distributions.

Probability · Mathematics 2018-12-14 Vadim Gorin , Sasha Sodin

In several applications, one must estimate a real-valued (symmetric) Toeplitz covariance matrix, typically shifted by the conjugated diagonal matrices of phase progression and phase "calibration" errors. Unlike the Hermitian Toeplitz…

Signal Processing · Electrical Eng. & Systems 2025-07-03 Yuri Abramovich , Victor Abramovich , Tanit Pongsiri

We consider some random band matrices with band-width $N^\mu$ whose entries are independent random variables with distribution tail in $x^{-\alpha}$. We consider the largest eigenvalues and the associated eigenvectors and prove the…

Probability · Mathematics 2015-06-25 Florent Benaych-Georges , Sandrine Péché

We establish a comprehensive probability theory for coherent transport of random waves through arbitrary linear media. The transmissivity distribution for random coherent waves is a fundamental B-spline with knots at the transmission…

Optics · Physics 2025-11-07 Yunrui Wang , Cheng Guo

In this paper, we characterize the asymptotic and large scale behavior of the eigenvalues of wavelet random matrices in high dimensions. We assume that possibly non-Gaussian, finite-variance $p$-variate measurements are made of a…

Statistics Theory · Mathematics 2024-06-11 Patrice Abry , B. Cooper Boniece , Gustavo Didier , Herwig Wendt

In this paper, we consider the singular values and singular vectors of finite, low rank perturbations of large rectangular random matrices. Specifically, we prove almost sure convergence of the extreme singular values and appropriate…

Probability · Mathematics 2012-01-27 Florent Benaych-Georges , Raj Rao Nadakuditi

We compute the asymptotic empirical eigenvalue distribution of the matrix $M = \bigodot_{i=1}^k \frac{1}{d_i}X^{(i)}{X^{(i)}}^\top$ where $X^{(i)}\in\mathbb{R}^{n\times d_i}$ are independent matrices with independent rows but general…

Probability · Mathematics 2026-01-14 Lucas Benigni , Ziyad Zaklani

In this paper we study an ensemble of random matrices called Elliptic Volatility Model, which arises in finance as models of stock returns. This model consists of a product of independent matrices $X = \Sigma Z $ where $Z$ is a $T$ by $S$…

Probability · Mathematics 2024-02-06 Anna Maltsev , Svetlana Malysheva

For piecewise expanding one-dimensional maps without periodic turning points we prove that isolated eigenvalues of small (random) perturbations of these maps are close to isolated eigenvalues of the unperturbed system. (Here ``eigenvalue''…

chao-dyn · Physics 2009-10-30 Michael Blank , Gerhard Keller

The purpose of this paper is to establish universality of the fluctuations of the largest eigenvalue of some non necessarily Gaussian complex Deformed Wigner Ensembles. The real model is also considered. Our approach is close to the one…

Probability · Mathematics 2015-06-26 Delphine Féral , Sandrine Péché

We review our recent results on pseudo-hermitian random matrix theory which were hitherto presented in various conferences and talks. (Detailed accounts of our work will appear soon in separate publications.) Following an introduction of…

Mathematical Physics · Physics 2021-10-27 Joshua Feinberg , Roman Riser

A probabilistic representation for a class of weighted $p$-radial distributions, based on mixtures of a weighted cone probability measure and a weighted uniform distribution on the Euclidean $\ell_p^n$-ball, is derived. Large deviation…

Probability · Mathematics 2022-06-01 Tom Kaufmann , Christoph Thaele