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We derive a non-asymptotic expression for the moments of traces of monomials in several independent complex Wishart matrices, extending some explicit formulas available in the literature. We then deduce the explicit expression for the…

Probability · Mathematics 2008-08-30 Wlodek Bryc

We prove that any non commutative polynomial of r independent copies of Wigner matrices converges a.s. towards the polynomial of r free semicircular variables in operator norm. This result extends a previous work of Haagerup and…

Probability · Mathematics 2007-05-23 Mireille Capitaine , Catherine Donati-Martin

The celebrated Mar\v{c}enko-Pastur law, that considers the asymptotic spectral density of random covariance matrices, has found a great number of applications in physics, biology, economics, engineering, among others. Here, using techniques…

Disordered Systems and Neural Networks · Physics 2022-05-17 Isaac Pérez Castillo

Let $X_N$ be a $N \times N$ real Wishart random matrix with aspect ratio $M/N$. The limit eigenvalue distribution of $X_N$ is the Marchenko-Pastur law with parameter $c = \lim_N M/N$. The limit moments $\{m_n\}_n$ are given by $m_n =…

Probability · Mathematics 2025-07-30 James A. Mingo , Josue Vazquez-Becerra

A non-Hermitean extension of paradigmatic Wishart random matrices is introduced to set up a theoretical framework for statistical analysis of (real, complex and real quaternion) stochastic time series representing two "remote" complex…

Mathematical Physics · Physics 2011-02-07 Eugene Kanzieper , Navinder Singh

In random matrix theory, Marchenko-Pastur law states that random matrices with independent and identically distributed entries have a universal asymptotic eigenvalue distribution under large dimension limit, regardless of the choice of…

High Energy Physics - Theory · Physics 2015-05-12 Xiaochuan Lu , Hitoshi Murayama

We consider the complex eigenvalues of a Wishart type random matrix model $X=X_1 X_2^*$, where two rectangular complex Ginibre matrices $X_{1,2}$ of size $N\times (N+\nu)$ are correlated through a non-Hermiticity parameter $\tau\in[0,1]$.…

Probability · Mathematics 2021-03-26 Gernot Akemann , Sung-Soo Byun , Nam-Gyu Kang

Random matrix theory has become a cornerstone in modern statistics and data science, providing fundamental tools for understanding high-dimensional covariance structures. Within this framework, the Wishart matrix plays a central role in…

Statistics Theory · Mathematics 2025-11-26 Fengcheng Liu

We study the behavior of a real $p$-dimensional Wishart random matrix with $n$ degrees of freedom when $n,p\rightarrow\infty$ but $p/n\rightarrow 0$. We establish the existence of phase transitions when $p$ grows at the order…

Probability · Mathematics 2017-05-11 Didier Chételat , Martin T. Wells

We investigate the asymptotic behavior of the empirical eigenvalues distribution of the partial transpose of a random quantum state. The limiting distribution was previously investigated via Wishart random matrices indirectly (by…

Mathematical Physics · Physics 2013-07-16 Motohisa Fukuda , Piotr Śniady

We investigate random matrices whose entries are obtained by applying a nonlinear kernel function to pairwise inner products between $n$ independent data vectors, drawn uniformly from the unit sphere in $\mathbb{R}^d$. This study is…

Probability · Mathematics 2023-05-09 Yue M. Lu , Horng-Tzer Yau

For random matrix ensembles with non-gaussian matrix elements that may exhibit some correlations, it is shown that centered traces of polynomials in the matrix converge in distribution to a Gaussian process whose covariance matrix is…

Mathematical Physics · Physics 2009-04-24 Jeffrey Schenker , Hermann Schulz-Baldes

In this paper we consider a new normalization of matrices obtained by choosing distinct codewords at random from linear codes over finite fields and find that under some natural algebraic conditions of the codes their empirical spectral…

Information Theory · Computer Science 2018-08-29 Chin Hei Chan , Enoch Kung , Maosheng Xiong

These lecture notes provide a comprehensive, self-contained introduction to the analysis of Wishart matrix moments. This study may act as an introduction to some particular aspects of random matrix theory, or as a self-contained exposition…

Probability · Mathematics 2019-02-12 Adrian N. Bishop , Pierre Del Moral , Angele Niclas

It is well known the sample covariance has a consistent bias in the spectrum, for example spectrum of Wishart matrix follows the Marchenko-Pastur law. We in this work introduce an iterative algorithm 'Concent' that actively eliminate this…

Machine Learning · Statistics 2022-01-04 Juntao Duan , Ionel Popescu , Heinrich Matzinger

Based on the multivariate saddle point method we study the asymptotic behavior of the characteristic polynomials associated to Wishart type random matrices that are formed as products consisting of independent standard complex Gaussian and…

Classical Analysis and ODEs · Mathematics 2014-07-11 Thorsten Neuschel , Dries Stivigny

We study asymptotic distributions of large dimensional random matrices of the form $BB^{*}$, where $B$ is a product of $p$ rectangular random matrices, using free probability and combinatorics of colored labeled noncrossing partitions.…

Probability · Mathematics 2020-04-03 Romuald Lenczewski , Rafał Sałapata

The complex Wishart ensemble is the statistical ensemble of $M \times N$ complex random matrices with $M \geq N$ such that the real and imaginary parts of each element are given by independent standard normal variables. The Marcenko--Pastur…

Probability · Mathematics 2021-07-06 Taiki Endo , Makoto Katori

We show how the replica method can be used to compute the asymptotic eigenvalue spectrum of a real Wishart product matrix. For unstructured factors, this provides a compact, elementary derivation of a polynomial condition on the Stieltjes…

Disordered Systems and Neural Networks · Physics 2023-01-24 Jacob A. Zavatone-Veth , Cengiz Pehlevan

We study the spectrum of generalized Wishart matrices, defined as $\mathbf{F}=( X Y^\top + Y X^\top)/2T$, where $X$ and $Y$ are $N \times T$ matrices with zero mean, unit variance IID entries and such that $\mathbb{E}[X_{it} Y_{jt}]=c…

Disordered Systems and Neural Networks · Physics 2021-01-04 Jean-Philippe Bouchaud , Marc Potters
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