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The current work applies some recent combinatorial tools due to Jain to control the eigenvalue gaps of a matrix $M_n = M + N_n$ where $M$ is deterministic, symmetric with large operator norm and $N_n$ is a random symmetric matrix with…

Probability · Mathematics 2022-11-02 Kyle Luh , Ryan Vogel , Alan Yu

This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large $p$, large $n$" scenario, where $p$ represents the number of variables and $n$ is the sample size. Our analysis…

Statistics Theory · Mathematics 2026-02-02 Partha Sarkar , Kshitij Khare , Malay Ghosh , Matt P. Wand

A class of 2x2 random-matrix models is introduced for which the Brody distribution is the exact eigenvalue spacing distribution. The matrix elements consist of constrained finite sums of an exponential random variable raised to various…

Mathematical Physics · Physics 2025-08-07 Jamal Sakhr

We prove a large deviation result for a random symmetric n x n matrix with independent identically distributed entries to have a few eigenvalues of size n. If the spectrum S survives when the matrix is rescaled by a factor of n, it can only…

Probability · Mathematics 2013-04-22 Sourav Chatterjee , S. R. S. Varadhan

The eigenvalues of quantum chaotic systems have been conjectured to follow, in the large energy limit, the statistical distribution of eigenvalues of random ensembles of matrices of size $N\rightarrow\infty$. Here we provide semiclassical…

Chaotic Dynamics · Physics 2011-12-07 P. Leboeuf , A. G. Monastra

The structure function of a random matrix ensemble can be specified as the covariance of the linear statistics $\sum_{j=1}^N e^{i k_1 \lambda_j}$, $\sum_{j=1}^N e^{-i k_2 \lambda_j}$ for Hermitian matrices, and the same with the eigenvalues…

Mathematical Physics · Physics 2021-05-26 Peter J. Forrester

Random matrix theory has played an important role in various areas of pure mathematics, mathematical physics, and machine learning. From a practical perspective of data science, input data are usually normalized prior to processing. Thus,…

Machine Learning · Computer Science 2025-12-18 Hyakka Nakada , Shu Tanaka

Statistical properties of non--symmetric real random matrices of size $M$, obtained as truncations of random orthogonal $N\times N$ matrices are investigated. We derive an exact formula for the density of eigenvalues which consists of two…

Statistical Mechanics · Physics 2010-10-21 Boris A. Khoruzhenko , Hans-Juergen Sommers , Karol Zyczkowski

Consider an ensemble of $N\times N$ non-Hermitian matrices in which all entries are independent identically distributed complex random variables of mean zero and absolute mean-square one. If the entry distributions also possess bounded…

Probability · Mathematics 2007-05-23 B. Rider , Jack W. Silverstein

We compute all massive partition functions or characteristic polynomials and their complex eigenvalue correlation functions for non-Hermitean extensions of the symplectic and chiral symplectic ensemble of random matrices. Our results are…

Mathematical Physics · Physics 2008-11-26 G. Akemann , F. Basile

We calculate analytically, for finite-size matrices, joint probability densities of ratios of level spacings in ensembles of random matrices characterized by their associated confining potential. We focus on the ratios of two spacings…

Quantum Physics · Physics 2014-03-18 Y. Y. Atas , E. Bogomolny , O. Giraud , P. Vivo , E. Vivo

We introduce a random two-matrix model interpolating between a chiral Hermitian (2n+nu)x(2n+nu) matrix and a second Hermitian matrix without symmetries. These are taken from the chiral Gaussian Unitary Ensemble (chGUE) and Gaussian Unitary…

Mathematical Physics · Physics 2011-11-03 Gernot Akemann , Taro Nagao

We consider products of independent random matrices with independent entries. The limit distribution of the expected empirical distribution of eigenvalues of such products is computed. Let $X^{(\nu)}_{jk},{}1\le j,r\le n$, $\nu=1,...,m$ be…

Probability · Mathematics 2011-04-27 Friedrich Götze , Alexander Tikhomirov

Statistical properties of ensembles of random density matrices are investigated. We compute traces and von Neumann entropies averaged over ensembles of random density matrices distributed according to the Bures measure. The eigenvalues of…

Quantum Physics · Physics 2009-11-10 Hans-Juergen Sommers , Karol Zyczkowski

The Ginibre ensemble of nonhermitean random Hamiltonian matrices $K$ is considered. Each quantum system described by $K$ is a dissipative system and the eigenenergies $Z_{i}$ of the Hamiltonian are complex-valued random variables. The…

Statistical Mechanics · Physics 2007-05-23 Maciej M. Duras

We show that the quantum Hamilton Jacobi approach to a class of quantum mechanical bound state problems and the Gaussian orthogonal ensemble of random matrix theory are equivalent. The Berry connection for both problems is identical to…

Quantum Physics · Physics 2018-01-03 K. V. S. Shiv Chaitanya , B. A. Bambah

One-dimensional free fermions are studied with emphasis on propagating fronts emerging from a step initial condition. The probability distribution of the number of particles at the edge of the front is determined exactly. It is found that…

Statistical Mechanics · Physics 2013-02-08 Viktor Eisler , Zoltan Racz

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

In spite of its simplicity, the central limit theorem captures one of the most outstanding phenomena in mathematical physics, that of universality. While this classical result is well understood it is still not very clear what happens to…

Disordered Systems and Neural Networks · Physics 2023-04-19 Ernesto Carro , Luis Benet , Isaac Pérez Castillo

We apply the recently introduced method of hermitization to study in the large $N$ limit non-hermitean random matrices that are drawn from a large class of circularly symmetric non-Gaussian probability distributions, thus extending the…

Disordered Systems and Neural Networks · Physics 2009-10-30 J. Feinberg , A. Zee
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