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We describe Generalized Hermitian matrices ensemble sometimes called Chiral ensemble. We give global asymptotic of the density of eigenvalues or the statistical density. We will calculate a Laplace transform of such a density for finite…

Probability · Mathematics 2014-09-02 Mohamed Bouali

We investigate the universality of microscopic eigenvalue correlations for Random Matrix Theories with the global symmetries of the QCD partition function. In this article we analyze the case of real valued chiral Random Matrix Theories…

High Energy Physics - Theory · Physics 2008-11-26 B. Klein , J. J. M. Verbaarschot

Consider a random simplex $[X_1,\ldots,X_n]$ defined as the convex hull of independent identically distributed random points $X_1,\ldots,X_n$ in $\mathbb{R}^{n-1}$ with the following beta density: $$ f_{n-1,\beta} (x) \propto…

Probability · Mathematics 2020-07-14 Zakhar Kabluchko

We define a random commuting $d$-tuple of $n$-by-$n$ matrices to be a random variable that takes values in the set of commuting $d$-tuples and has a distribution that is a rapidly decaying continuous weight on this algebraic set. In the…

Probability · Mathematics 2025-05-15 John E. McCarthy

One can identify a tripartite classification of random matrix ensembles into geometrical universality classes corresponding to the plane, the sphere and the anti-sphere. The plane is identified with Ginibre-type (iid) matrices and the…

Mathematical Physics · Physics 2015-06-11 Anthony Mays

We demonstrate the convergence of the characteristic polynomial of several random matrix ensembles to a limiting universal function, at the microscopic scale. The random matrix ensembles we treat are classical compact groups and the…

Probability · Mathematics 2019-02-05 Reda Chhaibi , Emma Hovhannisyan , Joseph Najnudel , Ashkan Nikeghbali , Brad Rodgers

We study limiting distribution of pair counting statistics of the form $ \sum_{1\leq i\neq j\leq N} f(L_N\*(\theta_i-\theta_j))$ for the circular $\beta$-ensemble (C$\beta$E) of random matrices for sufficiently smooth test function $f$ and…

Probability · Mathematics 2021-11-18 Ander Aguirre , Alexander Soshnikov , Joshua Sumpter

In this article we recover the distribution function (and possible density) of an arbitrary random variable that is subject to an additive measurement error. This problem is also known as deconvolution and has a long tradition in…

Statistics Theory · Mathematics 2025-10-07 Henrik Kaiser

Recently we introduced a family of $U(N)$ invariant Random Matrix Ensembles which is characterized by a parameter $\lambda$ describing logarithmic soft-confinement potentials $V(H) \sim [\ln H]^{(1+\lambda)} \:(\lambda>0$). We showed that…

Disordered Systems and Neural Networks · Physics 2013-05-29 Jinmyung Choi , K. A. Muttalib

We construct a very general family of characteristic functions describing Random Matrix Ensembles (RME) having a global unitary invariance, and containing an arbitrary, one-variable probability measure which we characterize by a `spread…

Other Condensed Matter · Physics 2009-11-11 K. A. Muttalib , J. R. Klauder

Conditional on the extended Riemann hypothesis, we show that with high probability, the characteristic polynomial of a random symmetric $\{\pm 1\}$-matrix is irreducible. This addresses a question raised by Eberhard in recent work. The main…

Probability · Mathematics 2021-06-09 Asaf Ferber , Vishesh Jain , Ashwin Sah , Mehtaab Sawhney

The eigenvalue PDF for some well known classes of non-Hermitian random matrices --- the complex Ginibre ensemble for example --- can be interpreted as the Boltzmann factor for one-component plasma systems in two-dimensional domains. We…

Mathematical Physics · Physics 2016-04-20 Peter J. Forrester

We derive the joint probability distribution of the first two spectral moments for the G$\beta$E random matrix ensembles in N dimensions for any N. This is achieved by making use of two complementary invariants of the domain in…

Mathematical Physics · Physics 2016-08-08 Tomasz Maciążek , Christopher H. Joyner , Uzy Smilansky

We analyze gene co-expression network under the random matrix theory framework. The nearest neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral…

Molecular Networks · Quantitative Biology 2015-05-18 Sarika Jalan , Norbert Solymosi , Gabör Vattay , Baowen Li

We propose a second-order accurate method to estimate the eigenvectors of extremely large matrices thereby addressing a problem of relevance to statisticians working in the analysis of very large datasets. More specifically, we show that…

Numerical Analysis · Mathematics 2010-02-05 Noureddine El Karoui , Alexandre d'Aspremont

We prove universality at the edge of the spectrum for unitary (beta=2), orthogonal (beta=1) and symplectic (beta=4) ensembles of random matrices in the scaling limit for a class of weights w(x)=exp(-V(x)) where V is a polynomial,…

Mathematical Physics · Physics 2007-05-23 Percy Deift , Dimitri Gioev

We consider pairs of anti-commuting $2p$-by-$2p$ Hermitian matrices that are chosen randomly with respect to a Gaussian measure. Generically such a pair decomposes into the direct sum of $2$-by-$2$ blocks on which the first matrix has…

Probability · Mathematics 2023-12-25 John E. McCarthy , Hazel T. McCarthy

In this tutorial, exponentiation and factorization (decomposition) formulas are derived and discussed for common matrix operators that arise in studies of classical dynamics, linear and nonlinear optics, and special relativity. To…

Optics · Physics 2025-08-26 C. J. McKinstrie , M. V. Kozlov

A remarkable property of Hermitian ensembles is their universal behavior, that is, once properly rescaled the eigenvalue statistics does not depend on particularities of the ensemble. Recently, normal matrix ensembles have attracted…

Mathematical Physics · Physics 2009-09-21 Alexei M. Veneziani , Tiago Pereira , Domingos H. U. Marchetti

This paper presents an algorithmic method for generating random orthogonal matrices \(A\) that satisfy the property \(A^t S A = S\), where \(S\) is a fixed real invertible symmetric or skew-symmetric matrix. This method is significant as it…

Numerical Analysis · Mathematics 2024-12-19 Ali Saraeb