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In the paper, multivariate probability distributions are considered that are representable as scale mixtures of multivariate elliptically contoured stable distributions. It is demonstrated that these distributions form a special subclass of…

Probability · Mathematics 2019-12-05 Victor Korolev , Alexander Zeifman

In this paper we show that the empirical eigenvalue distribution of any sample covariance matrix generated by independent copies of a stationary regular sequence has a limiting distribution depending only on the spectral density of the…

Probability · Mathematics 2014-08-12 Florence Merlevede , Magda Peligrad

In this paper, we consider the singular values and singular vectors of low rank perturbations of large rectangular random matrices, in the regime the matrix is "long": we allow the number of rows (columns) to grow polynomially in the number…

Probability · Mathematics 2021-10-22 Gérard Ben Arous , Daniel Zhengyu Huang , Jiaoyang Huang

Linial-Meshulam complex is a random simplicial complex on $n$ vertices with a complete $(d-1)$-dimensional skeleton and $d$-simplices occurring independently with probability p. Linial-Meshulam complex is one of the most studied…

Probability · Mathematics 2023-02-23 Kartick Adhikari , Kiran Kumar A. S. , Koushik Saha

We show central limit theorems (CLT) for the Stieltjes transforms or more general analytic functions of symmetric matrices with independent heavy tailed entries, including entries in the domain of attraction of $\alpha$-stable laws and…

Probability · Mathematics 2015-06-12 Florent Benaych-Georges , Alice Guionnet , Camille Male

In this paper, we establish the central limit theorem (CLT) for linear spectral statistics (LSS) of large-dimensional sample covariance matrix when the population covariance matrices are not uniformly bounded, which is a nontrivial…

Statistics Theory · Mathematics 2022-05-17 Zhijun Liu , Jiang Hu , Zhidong Bai , Haiyan Song

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

In this article we investigate high-dimensional banded sample covariance matrices under the regime that the sample size $n$, the dimension $p$ and the bandwidth $d$ tend simultaneously to infinity such that $$n/p\to 0 \ \ \text{and} \ \…

Probability · Mathematics 2015-08-27 Kamil Jurczak

We derive a set of constraints, which we will call hierarchy constraints (HCs), on scattering amplitudes of an arbitrary multistate Landau-Zener model (MLZM). The presence of additional symmetries can transform such constraints into…

Quantum Physics · Physics 2017-02-08 N. A. Sinitsyn , J. Lin , V. Y. Chernyak

We investigate the level spacing distribution for three ensembles of real symmetric matrices having additional structural constraint to reduce the number of independent entries to only $ (n+1)/2 $ in contrast to the $ n(n+1)/2 $ for a real…

Mathematical Physics · Physics 2022-12-13 Md. Sabir Ali , Shashi C. L. Srivastava

Resistance \rho of an one-dimensional disordered system of length l has the log-normal distribution in the limit of large l. Parameters of this distribution depend on the Fermi level position, but are independent on the boundary conditions.…

Disordered Systems and Neural Networks · Physics 2023-10-11 I. M. Suslov

High-dimensional sample correlation matrices are a crucial class of random matrices in multivariate statistical analysis. The central limit theorem (CLT) provides a theoretical foundation for statistical inference. In this paper, assuming…

Statistics Theory · Mathematics 2024-08-30 Weijiang Chen , Shurong Zheng , Tingting Zou

Spectral properties of random matrices play an important role in statistics, machine learning, communications, and many other areas. Engaging results regarding the convergence of the empirical spectral distribution (ESD) and the…

Statistics Theory · Mathematics 2025-07-08 Zeyan Zhuang , Xin Zhang , Dongfang Xu , Shenghui Song

We study the spectral properties of a class of random matrices where the matrix elements depend exponentially on the distance between uniformly and randomly distributed points. This model arises naturally in various physical contexts, such…

Disordered Systems and Neural Networks · Physics 2015-05-18 Ariel Amir , Yuval Oreg , Yoseph Imry

We study a class of random matrices that appear in several communication and signal processing applications, and whose asymptotic eigenvalue distribution is closely related to the reconstruction error of an irregularly sampled bandlimited…

Information Theory · Computer Science 2008-06-24 Alessandro Nordio , Carla-Fabiana Chiasserini , Emanuele Viterbo

Singular Spectrum Analysis (SSA) occupies a prominent place in the real signal analysis toolkit alongside Fourier and Wavelet analysis. In addition to the two aforementioned analyses, SSA allows the separation of patterns directly from the…

It is well known that square matrices with independent and identically distributed (iid) random entries are typically well conditioned. A natural question is whether this favorable behavior persists for random matrices whose entries obey…

Probability · Mathematics 2026-02-16 Paulo Manrique

For a class of symmetric random matrices whose entries are martingale differences adapted to an increasing filtration, we prove that under a Lindeberg-like condition, the empirical spectral distribution behaves asymptotically similarly to a…

Probability · Mathematics 2014-02-27 Florence Merlevède , Costel Peligrad , Magda Peligrad

For fixed positive integers m, we consider the product of m independent n by n random matrices with iid entries as in the limit as n tends to infinity. Under suitable assumptions on the entries of each matrix, it is known that the limiting…

Probability · Mathematics 2017-11-21 Natalie Coston , Sean O'Rourke , Philip Matchett Wood

Scattering is an important phenomenon which is observed in systems ranging from the micro- to macroscale. In the context of nuclear reaction theory the Heidelberg approach was proposed and later demonstrated to be applicable to many chaotic…

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