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We consider the number of crossings in a graph which is embedded randomly on a convex set of points. We give an estimate to the normal distribution in Kolmogorov distance which implies a convergence rate of order $n^{-1/2}$ for various…

Combinatorics · Mathematics 2022-08-26 Santiago Arenas-Velilla , Octavio Arizmendi

By the use of extensive numerical simulations we show that the nearest-neighbor energy level spacing distribution $P(s)$ and the entropic eigenfunction localization length of the adjacency matrices of Erd\H{o}s-R\'enyi (ER) {\it fully}…

Disordered Systems and Neural Networks · Physics 2015-06-24 J. A. Mendez-Bermudez , A. Alcazar-Lopez , A. J. Martinez-Mendoza , Francisco A. Rodrigues , Thomas K. DM. Peron

Extremal spacings between eigenvalues of random unitary matrices of size N pertaining to circular ensembles are investigated. Explicit probability distributions for the minimal spacing for various ensembles are derived for N = 4. We study…

Mathematical Physics · Physics 2013-11-13 Marek Smaczynski , Tomasz Tkocz , Marek Kus , Karol Zyczkowski

We consider the adjacency matrix of the ensemble of Erd\H{o}s-R\'enyi random graphs which consists of graphs on $N$ vertices in which each edge occurs independently with probability $p$. We prove that in the regime $pN \gg 1$ these matrices…

Probability · Mathematics 2016-01-20 Jiaoyang Huang , Benjamin Landon , Horng-Tzer Yau

Results regarding probable bifurcations from fixed points are presented in the context of general dynamical systems (real, random matrices), time-delay dynamical systems (companion matrices), and a set of mappings known for their properties…

Chaotic Dynamics · Physics 2009-11-11 D. J. Albers , J. C. Sprott

We show that, under mild assumptions, the spectrum of a sum of independent random matrices is close to that of the Gaussian random matrix whose entries have the same mean and covariance. This nonasymptotic universality principle yields…

Probability · Mathematics 2024-06-26 Tatiana Brailovskaya , Ramon van Handel

This paper investigates global and local laws for sample covariance matrices with general growth rates of dimensions. The sample size $N$ and population dimension $M$ can have the same order in logarithm, which implies that their ratio…

Statistics Theory · Mathematics 2025-11-05 Bing-Yi Jing , Weiming Li , Jiahui Xie , Yangchun Zhang , Wang Zhou

We consider finite point subsets (distributions) in compact metric spaces. In the case of general rectifiable metric spaces, non-trivial bounds for sums of distances between points of distributions and for discrepancies of distributions in…

Metric Geometry · Mathematics 2017-01-17 M. M. Skriganov

We consider large Hermitian matrices whose entries are defined by evaluating the exponential function along orbits of the skew-shift $\binom{j}{2} \omega+jy+x \mod 1$ for irrational $\omega$. We prove that the eigenvalue distribution of…

Mathematical Physics · Physics 2021-07-14 Arka Adhikari , Marius Lemm , Horng-Tzer Yau

In these lectures we discuss some elementary concepts in connection with the theory of symmetric spaces applied to ensembles of random matrices. We review how the relationship between random matrix theory and symmetric spaces can be used in…

Mathematical Physics · Physics 2007-05-23 Ulrika Magnea

We confirm universal behaviors such as eigenvalue distribution and spacings predicted by Random Matrix Theory (RMT) for the cross correlation matrix of the daily stock prices of Tokyo Stock Exchange from 1993 to 2001, which have been…

Statistical Mechanics · Physics 2009-11-10 Akihiko Utsugi , Kazusumi Ino , Masaki Oshikawa

We consider symmetric and Hermitian random matrices whose entries are independent and symmetric random variables with an arbitrary variance pattern. Under a novel Short-to-Long Mixing condition, which is sharp in the sense that it precludes…

Probability · Mathematics 2025-11-12 Dang-Zheng Liu , Guangyi Zou

We study the distribution of the least singular value associated to an ensemble of sparse random matrices. Our motivating example is the ensemble of $N\times N$ matrices whose entries are chosen independently from a Bernoulli distribution…

Probability · Mathematics 2019-01-25 Ziliang Che , Patrick Lopatto

We consider an $N$ by $N$ real symmetric random matrix $X=(x_{ij})$ where $\mathbb{E}x_{ij}x_{kl}=\xi_{ijkl}$. Under the assumption that $(\xi_{ijkl})$ is the discretization of a piecewise Lipschitz function and that the correlation is…

Probability · Mathematics 2016-04-22 Ziliang Che

We propose the existence of a new universality in classical chaotic systems when the number of degrees of freedom is large: the statistical property of the Lyapunov spectrum is described by Random Matrix Theory. We demonstrate it by…

High Energy Physics - Theory · Physics 2018-03-13 Masanori Hanada , Hidehiko Shimada , Masaki Tezuka

Let $G$ be a large (simple, unlabeled) dense graph on $n$ vertices. Suppose that we only know, or can estimate, the empirical distribution of the number of subgraphs $F$ that each vertex in $G$ participates in, for some fixed small graph…

Information Theory · Computer Science 2023-08-08 Shahar Stein Ioushua , Ofer Shayevitz

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

The random matrix uniformly distributed over the set of all m-by-n matrices over a finite field plays an important role in many branches of information theory. In this paper a generalization of this random matrix, called k-good random…

Information Theory · Computer Science 2012-05-03 Shengtian Yang , Thomas Honold

This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form $\mathcal{W}_N=\Sigma^{1/2}XX^*\Sigma ^{1/2}$. Here, $X=(x_{ij})_{M,N}$ is an…

Probability · Mathematics 2015-03-06 Zhigang Bao , Guangming Pan , Wang Zhou

We provide finite-sample distribution approximations, that are uniform in the parameter, for inference in linear mixed models. Focus is on variances and covariances of random effects in cases where existing theory fails because their…

Statistics Theory · Mathematics 2025-07-29 Karl Oskar Ekvall , Matteo Bottai
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