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We consider a random matrix whose entries are independent Gaussian variables taking values in the field of quaternions with variance $1/n$. Using logarithmic potential theory, we prove the almost sure convergence, as the dimension $n$ goes…

Probability · Mathematics 2011-09-05 Florent Benaych-Georges , Francois Chapon

We present the results of systematic numerical computations relating to the extreme value statistics of the characteristic polynomials of random unitary matrices drawn from the Circular Unitary Ensemble (CUE) of Random Matrix Theory. In…

Statistical Mechanics · Physics 2018-10-24 Yan V. Fyodorov , Sven Gnutzmann , Jonathan P. Keating

We consider a class of matrix integrals over the unitary group $U(N)$ with an infinite set of couplings characterized by a series $f(q)=\sum_{n \ge 1} a_n q^n$, with $a_n \in \mathbb{Z}$. Such integrals arise in physics as the partition…

High Energy Physics - Theory · Physics 2023-02-23 Sameer Murthy

This paper presents new probability inequalities for sums of independent, random, self-adjoint matrices. These results place simple and easily verifiable hypotheses on the summands, and they deliver strong conclusions about the…

Probability · Mathematics 2014-04-29 Joel A. Tropp

In this brief paper the probability density of a random real, complex and quaternion determinant is rederived using singular values. The behaviour of suitably rescaled random determinants is studied in the limit of infinite order of the…

Statistical Mechanics · Physics 2009-10-31 Giovanni M. Cicuta , Madan L. Mehta

Recently much effort has been made towards the introduction of non-Hermitian random matrix models respecting $PT$-symmetry. Here we show that there is a one-to-one correspondence between complex $PT$-symmetric matrices and split-complex and…

Mathematical Physics · Physics 2015-09-17 Eva-Maria Graefe , Steve Mudute-Ndumbe , Matthew Taylor

We review methods to calculate eigenvalue distributions of products of large random matrices. We discuss a generalization of the law of free multiplication to non-Hermitian matrices and give a couple of examples illustrating how to use…

Mathematical Physics · Physics 2015-06-17 Zdzislaw Burda

We study largest singular values of large random matrices, each with mean of a fixed rank $K$. Our main result is a limit theorem as the number of rows and columns approach infinity, while their ratio approaches a positive constant. It…

Probability · Mathematics 2021-03-02 Wlodek Bryc , Jack W. Silverstein

We consider the additive superimposition of an extensive number of independent Euclidean Random Matrices in the high-density regime. The resolvent is computed with techniques from free probability theory, as well as with the replica method…

Disordered Systems and Neural Networks · Physics 2020-05-27 Aldo Battista , Remi Monasson

According to Dyson's three fold way, from the viewpoint of global time reversal symmetry there are three circular ensembles of unitary random matrices relevant to the study of chaotic spectra in quantum mechanics. These are the circular…

Mathematical Physics · Physics 2017-02-24 Folkmar Bornemann , Peter J. Forrester , Anthony Mays

In the paper [25], written in collaboration with Gesine Reinert, we proved a universality principle for the Gaussian Wiener chaos. In the present work, we aim at providing an original example of application of this principle in the…

Probability · Mathematics 2010-02-08 Ivan Nourdin , Giovanni Peccati

We investigate the implications of free probability for random matrices. From rules for calculating all possible joint moments of two free random matrices, we develop a notion of partial freeness which is quantified by the breakdown of…

Probability · Mathematics 2013-05-23 Jiahao Chen , Troy Van Voorhis , Alan Edelman

In the last few years, the supersymmetry method was generalized to real-symmetric, Hermitean, and Hermitean self-dual random matrices drawn from ensembles invariant under the orthogonal, unitary, and unitary symplectic group, respectively.…

Mathematical Physics · Physics 2014-10-14 Vural Kaymak , Mario Kieburg , Thomas Guhr

We develop an algorithm for sampling from the unitary invariant random matrix ensembles. The algorithm is based on the representation of their eigenvalues as a determinantal point process whose kernel is given in terms of orthogonal…

Mathematical Physics · Physics 2014-04-02 Sheehan Olver , Raj Rao Nadakuditi , Thomas Trogdon

We prove Gaussian fluctuation for pair counting statistics of the form $ \sum_{1\leq i\neq j\leq N} f(\theta_i-\theta_j)$ for the Circular Unitary Ensemble (CUE) of random matrices in the case of a slowly growing variance in the limit of…

Probability · Mathematics 2021-02-03 Ander Aguirre , Alexander Soshnikov

Let H=A+UBU* where A and B are two N-by-N Hermitian matrices and U is a Haar-distributed random unitary matrix, and let \mu_H, \mu_A, and \mu_B be empirical measures of eigenvalues of matrices H, A, and B, respectively. Then, it is known…

Probability · Mathematics 2011-06-28 Vladislav Kargin

We develop a theory for the eigenvalue density of arbitrary non-Hermitian Euclidean matrices. Closed equations for the resolvent and the eigenvector correlator are derived. The theory is applied to the random Green's matrix relevant to wave…

Disordered Systems and Neural Networks · Physics 2011-08-26 A. Goetschy , S. E. Skipetrov

The zeros of the random Laurent series $1/\mu - \sum_{j=1}^\infty c_j/z^j$, where each $c_j$ is an independent standard complex Gaussian, is known to correspond to the scaled eigenvalues of a particular additive rank 1 perturbation of a…

Mathematical Physics · Physics 2018-07-19 Peter J. Forrester , Jesper R. Ipsen

The problem of iterated partial summations is solved for some discrete distributions defined on discrete supports. The power method, usually used as a computational approach to finding matrix eigenvalues and eigenvectors, is in some cases…

Probability · Mathematics 2019-01-28 Michaela Koscova , Radoslav Harman , Jan Macutek

The paper deals with distribution of singular values of product of random matrices arising in the analysis of deep neural networks. The matrices resemble the product analogs of the sample covariance matrices, however, an important…

Mathematical Physics · Physics 2020-11-23 Leonid Pastur