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We give a constructive proof for the superbosonization formula for invariant random matrix ensembles, which is the supersymmetry analog of the theory of Wishart matrices. Formulas are given for unitary, orthogonal and symplectic symmetry,…

Statistical Mechanics · Physics 2007-11-15 Hans-Jürgen Sommers

We study a generalization of the Wigner function to arbitrary tuples of hermitian operators, which is a distribution uniquely characterized by the property that the marginals for all linear combinations of the given operators agree with the…

Quantum Physics · Physics 2020-07-09 René Schwonnek , Reinhard F. Werner

Covariance matrix estimation concerns the problem of estimating the covariance matrix from a collection of samples, which is of extreme importance in many applications. Classical results have shown that $O(n)$ samples are sufficient to…

Information Theory · Computer Science 2019-03-19 Wei Cui , Xu Zhang , Yulong Liu

Consider a $N\times n$ matrix $\Sigma_n=\frac{1}{\sqrt{n}}R_n^{1/2}X_n$, where $R_n$ is a nonnegative definite Hermitian matrix and $X_n$ is a random matrix with i.i.d. real or complex standardized entries. The fluctuations of the linear…

Probability · Mathematics 2016-06-29 Jamal Najim , Jianfeng Yao

Consider the product $X = X_{1}\cdots X_{m}$ of $m$ independent $n\times n$ iid random matrices. When $m$ is fixed and the dimension $n$ tends to infinity, we prove Gaussian limits for the centered linear spectral statistics of $X$ for…

Probability · Mathematics 2019-04-11 Natalie Coston , Sean O'Rourke

We study $k$-point correlators of characteristic polynomials in non-Hermitian ensembles of random matrices, focusing on the real, complex and quaternion $N \times N$ Ginibre ensembles. Our approach is based on the technique of character…

Mathematical Physics · Physics 2024-07-15 Alexander Serebryakov , Nick Simm

Generalized linear (GL-) statistics are defined as functionals of an U-quantile process and unify different classes of statistics such as U-statistics and L-statistics. We derive a central limit theorem for GL-statistics of strongly mixing…

Statistics Theory · Mathematics 2014-12-02 Svenja Fischer , Roland Fried , Martin Wendler

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 area related to M. Liv\v{s}ic's characteristic matrix functions is too vast to be discussed in one paper and we selected for this article the problems which are close to our scientific interests. We discuss M.Liv\v{s}ic's results…

Classical Analysis and ODEs · Mathematics 2021-04-27 Lev Sakhnovich

In this article, we establish a near-optimal convergence rate for the CLT of linear eigenvalue statistics of Wigner matrices, in Kolmogorov-Smirnov distance. For all test functions $f\in C^5(\mathbb R)$, we show that the convergence rate is…

Probability · Mathematics 2021-03-22 Zhigang Bao , Yukun He

This paper studies the problem of estimating a covariance matrix from correlated sub-Gaussian samples. We consider using the correlated sample covariance matrix estimator to approximate the true covariance matrix. We establish…

Information Theory · Computer Science 2019-10-17 Xu Zhang , Wei Cui , Yulong Liu

Integral representations of hypergeometric functions proved to be a very useful tool for studying their properties. The purpose of this paper is twofold. First, we extend the known representations to arbitrary values of the parameters and…

Classical Analysis and ODEs · Mathematics 2016-10-06 D. Karp , J. L. López

The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown. We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the…

Statistics Theory · Mathematics 2012-11-15 Bing-Yi Jing , Guangming Pan , Qi-Man Shao , Wang Zhou

Rectangular real $N \times (N + \nu)$ matrices $W$ with a Gaussian distribution appear very frequently in data analysis, condensed matter physics and quantum field theory. A central question concerns the correlations encoded in the spectral…

Mathematical Physics · Physics 2015-03-10 G. Akemann , T. Guhr , M. Kieburg , R. Wegner , T. Wirtz

We study the renormalized real sample covariance matrix $H=X^TX/\sqrt{MN}-\sqrt{M/N}$ with $N/M\rightarrow0$ as $N, M\rightarrow \infty$ in this paper. And we always assume $M=M(N)$. Here $X=[X_{jk}]_{M\times N}$ is an $M\times N$ real…

Probability · Mathematics 2011-11-16 Zhigang Bao

The GN model of non-linear fiber propagation has been shown to overestimate the variance of non-linearity due to the signal Gaussianity approximation, leading to maximum reach predictions for realistic optical systems which may be…

Optics · Physics 2015-06-18 P. Poggiolini , G. Bosco , A. Carena , V. Curri , Y. Jiang , F. Forghieri

Following E. Wigner's original vision, we prove that sampling the eigenvalue gaps within the bulk spectrum of a fixed (deformed) Wigner matrix $H$ yields the celebrated Wigner-Dyson-Mehta universal statistics with high probability.…

Mathematical Physics · Physics 2024-04-18 Giorgio Cipolloni , László Erdős , Dominik Schröder

We study Wigner function value statistics of classically chaotic quantum maps on compact 2D phase space. We show that the Wigner function statistics of a random state is a Gaussian, with the mean value becoming negligible compared to the…

Quantum Physics · Physics 2007-05-23 Martin Horvat , Tomaz Prosen

In this paper, we derive nearly tight probabilistic norm bounds for a class of random matrices we call graph matrices. While the classical case of symmetric matrices with independent random entries (Wigner's matrices) is a special case, in…

Combinatorics · Mathematics 2021-04-30 Kwangjun Ahn , Dhruv Medarametla , Aaron Potechin

In this note, we define a Gaussian probability distribution over matrices. We prove some useful properties of this distribution, namely, the fact that marginalization, conditioning, and affine transformations preserve the matrix Gaussian…

Probability · Mathematics 2018-06-22 Shane Barratt
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