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We study the rate of convergence of the empirical spectral distribution of products of independent non-Hermitian random matrices to the power of the Circular Law. The distance to the deterministic limit distribution will be measured in…

Probability · Mathematics 2021-04-12 Jonas Jalowy

We consider two random matrix ensembles which are relevant for describing critical spectral statistics in systems with multifractal eigenfunction statistics. One of them is the Gaussian non-invariant ensemble which eigenfunction statistics…

Disordered Systems and Neural Networks · Physics 2009-11-04 V. E. Kravtsov

We consider non-Hermitian random matrices $X \in \mathbb{C}^{n \times n}$ with general decaying correlations between their entries. For large $n$, the empirical spectral distribution is well approximated by a deterministic density,…

Probability · Mathematics 2021-02-25 Johannes Alt , Torben Krüger

We prove a universal limit theorem for the halting time, or iteration count, of the power/inverse power methods and the QR eigenvalue algorithm. Specifically, we analyze the required number of iterations to compute extreme eigenvalues of…

Numerical Analysis · Mathematics 2017-01-10 Percy Deift , Thomas Trogdon

We consider uniform random permutations in proper substitution-closed classes and study their limiting behavior in the sense of permutons. The limit depends on the generating series of the simple permutations in the class. Under a mild…

We establish universality of local eigenvalue correlations in unitary random matrix ensembles (1/Z_n) |\det M|^{2\alpha} e^{-n\tr V(M)} dM near the origin of the spectrum. If V is even, and if the recurrence coefficients of the orthogonal…

Mathematical Physics · Physics 2009-11-10 A. B. J. Kuijlaars , M. Vanlessen

The diversity product and the diversity sum are two very important parameters for a good-performing unitary space time constellation. A basic question is what the maximal diversity product (or sum) is. In this paper we are going to derive…

Combinatorics · Mathematics 2007-07-16 Guangyue Han , Joachim Rosenthal

We investigate the properties of uniform doubly stochastic random matrices, that is non-negative matrices conditioned to have their rows and columns sum to 1. The rescaled marginal distributions are shown to converge to exponential…

Probability · Mathematics 2010-11-01 Sourav Chatterjee , Persi Diaconis , Allan Sly

Let $T$ be an $n\times n$ truncation of an $(n+\alpha)\times (n+\alpha)$ Haar distributed unitary matrix. We consider the disk counting statistics of the eigenvalues of $T$. We prove that as $n\to + \infty$ with $\alpha$ fixed, the…

Mathematical Physics · Physics 2023-05-17 Yacin Ameur , Christophe Charlier , Philippe Moreillon

The universality phenomenon asserts that the distribution of the eigenvalues of random matrix with i.i.d. zero mean, unit variance entries does not depend on the underlying structure of the random entries. For example, a plot of the…

Probability · Mathematics 2012-10-11 Philip Matchett Wood

In this paper we study a random matrix model with the chiral and flavor structure of the QCD Dirac operator and a temperature dependence given by the lowest Matsubara frequency. Using the supersymmetric method for random matrix theory, we…

High Energy Physics - Phenomenology · Physics 2009-10-28 A. D. Jackson , M. K. Şener , J. J. M. Verbaarschot

We consider Hermitian and symmetric random band matrices $H$ in $d \geq 1$ dimensions. The matrix elements $H_{xy}$, indexed by $x,y \in \Lambda \subset \Z^d$, are independent, uniformly distributed random variables if $\abs{x-y}$ is less…

Mathematical Physics · Physics 2015-05-18 Laszlo Erdos , Antti Knowles

One of the great miracles of random matrix theory is that, in the $N \to \infty$ limit, many otherwise intractable matrix problems with horrendously complicated finite-$N$ expressions admit remarkably simple and elegant asymptotic…

Disordered Systems and Neural Networks · Physics 2026-05-15 Pierre Bousseyroux , Marc Potters

We discuss the product of $M$ rectangular random matrices with independent Gaussian entries, which have several applications including wireless telecommunication and econophysics. For complex matrices an explicit expression for the joint…

Mathematical Physics · Physics 2013-11-13 Gernot Akemann , Jesper R. Ipsen , Mario Kieburg

We show that the linear statistics of eigenvalues of circulant matrix obey the Gaussian central limit theorem for a large class of input sequences.

Probability · Mathematics 2018-02-13 Kartick Adhikari , Koushik Saha

We consider matrix-valued processes described as solutions to stochastic differential equations of very general form. We study the family of the empirical measure-valued processes constructed from the corresponding eigenvalues. We show that…

Probability · Mathematics 2019-01-10 Jacek Małecki , José Luis Pérez

Consider an $N\times N$ hermitian random matrix with independent entries, not necessarily Gaussian, a so called Wigner matrix. It has been conjectured that the local spacing distribution, i.e. the distribution of the distance between…

Mathematical Physics · Physics 2009-10-31 Kurt Johansson

Deriving the time evolution of a distribution of probability (or a probability density matrix) is a problem encountered frequently in a variety of situations: for physical time, it could be a kinetic reaction study, while identifying time…

Probability · Mathematics 2010-11-16 Razvan Teodorescu

We investigate the eigenvalues statistics of ensembles of normal random matrices when their order N tends to infinite. In the model the eigenvalues have uniform density within a region determined by a simple analytic polynomial curve. We…

Probability · Mathematics 2009-09-08 Alexei M. Veneziani , Tiago Pereira , Domingos H. U. Marchetti

The eigenvalue density for members of the Gaussian orthogonal and unitary ensembles follows the Wigner semi-circle law. If the Gaussian entries are all shifted by a constant amount c/Sqrt(2N), where N is the size of the matrix, in the large…

Mathematical Physics · Physics 2009-04-21 Kevin E. Bassler , Peter J. Forrester , Norman E. Frankel