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We investigate the rank of random (symmetric) sparse matrices. Our main finding is that with high probability, any dependency that occurs in such a matrix is formed by a set of few rows that contains an overwhelming number of zeros. This…

Probability · Mathematics 2007-11-20 Kevin P. Costello , Van Vu

Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elements can have different variances and be correlated with each…

Disordered Systems and Neural Networks · Physics 2016-12-21 Alexander Kuczala , Tatyana O. Sharpee

We introduce a new broad and exible class of multivariate elliptically symmetric distributions in- cluding the elliptically symmetric logistic and multivariate normal. Various probabilistic properties of the new distribution are studied,…

Probability · Mathematics 2018-10-26 Chuancun Yin , Xiuyan Sha

Given a random quantum state of multiple distinguishable or indistinguishable particles, we provide an effective method, rooted in symplectic geometry, to compute the joint probability distribution of the eigenvalues of its one-body reduced…

Quantum Physics · Physics 2014-10-21 Matthias Christandl , Brent Doran , Stavros Kousidis , Michael Walter

The randomised Horn problem, in both its additive and multiplicative version, has recently drawn increasing interest. Especially, closed analytical results have been found for the rank-1 perturbation of sums of Hermitian matrices and…

Mathematical Physics · Physics 2021-11-11 Jiyuan Zhang , Mario Kieburg , Peter J. Forrester

The eigenvalue distribution is investigated for matrix models related via the localization to Chern-Simons-matter theories. An integral representation of the planar resolvent is used to derive the positions of the branch points of the…

High Energy Physics - Theory · Physics 2015-05-28 Takao Suyama

In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry {\it win-loss}. We present in…

Mathematical Physics · Physics 2015-06-17 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

This is an introductory note concerning the distribution vectors in a unitary representation of a Lie group. We discuss the definition of matrix coefficients associated with a pair of distributions and how one can compute them. Most of the…

Functional Analysis · Mathematics 2022-01-03 Hongyu He

This study presents a new procedure for necessary tests of multivariate normality based on the uniform distribution on the Stiefel manifold. We demonstrate that the test statistic, which is formed by the product of the scaled residual…

Statistics Theory · Mathematics 2026-03-16 Koki Shimizu , Toshiya Iwashita

An equation is obtained for the Stieltjes transform of the normalized distribution of singular values of non-symmetric band random matrices in the limit when the band width and rank of the matrix simultaneously tend to infinity. Conditions…

Mathematical Physics · Physics 2015-03-17 Anna Lytova , Leonid Pastur

The density of complex eigenvalues of random asymmetric $N\times N$ matrices is found in the large-$N$ limit. The matrices are of the form $H_0+A$ where $A$ is a matrix of $N^2$ independent, identically distributed random variables with…

Condensed Matter · Physics 2009-10-28 Boris A Khoruzhenko

This paper considers an extension of the multivariate symmetric Laplace distribution to matrix variate case. The symmetric Laplace distribution is a scale mixture of normal distribution. The maximum likelihood estimators (MLE) of the…

Statistics Theory · Mathematics 2025-09-18 Pooja Yadav , Tanuja Srivastava

This paper is concerned with the asymptotic empirical eigenvalue distribution of a non linear random matrix ensemble. More precisely we consider $M= \frac{1}{m} YY^*$ with $Y=f(WX)$ where $W$ and $X$ are random rectangular matrices with…

Probability · Mathematics 2022-01-14 Lucas Benigni , Sandrine Péché

This is a review of the Riemann-Hilbert approach to the large $N$ asymptotics in random matrix models and its applications. We discuss the following topics: random matrix models and orthogonal polynomials, the Riemann-Hilbert approach to…

Mathematical Physics · Physics 2008-06-26 Pavel M. Bleher

Inequalities for norms of different versions of the geometric mean of two positive definite matrices are presented.

Functional Analysis · Mathematics 2015-02-17 Rajendra Bhatia , Priyanka Grover

Asymmetric causality tests are increasingly gaining popularity in different scientific fields. This approach corresponds better to reality since logical reasons behind asymmetric behavior exist and need to be considered in empirical…

Econometrics · Economics 2024-10-10 Abdulnasser Hatemi-J

One considers certain degenerations of the generic symmetric matrix over a field $k$ of characteristic zero and the main structures related to the determinant $f$ of the matrix, such as the ideal generated by its partial derivatives, the…

Commutative Algebra · Mathematics 2018-04-04 Rainelly Cunha , Zaqueu Ramos , Aron Simis

Non-asymptotic theory of random matrices strives to investigate the spectral properties of random matrices, which are valid with high probability for matrices of a large fixed size. Results obtained in this framework find their applications…

Probability · Mathematics 2013-08-02 Mark Rudelson

We discuss the possibility of deriving an H-theorem for the nonlinear discrete time evolution known as Ulam's redistribution of energy problem. In this model particles are paired at random and then their total energy is redistributed…

Statistical Mechanics · Physics 2013-06-06 S. M. Apenko

The distribution of products of random matrices chosen from fixed spherical classes is determined for classical rank 1 symmetric spaces. It is observed that $n\to\infty$ limit behaves approximately as in the abelian case. A theorem on the…

Representation Theory · Mathematics 2007-05-23 Jafar Shaffaf