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For a large $n\times m$ Gaussian matrix, we compute the joint statistics, including large deviation tails, of generalized and total variance - the scaled log-determinant $H$ and trace $T$ of the corresponding $n\times n$ covariance matrix.…

Statistical Mechanics · Physics 2016-04-29 Fabio Deelan Cunden , Pierpaolo Vivo

We establish a large-deviations principle for the largest eigenvalue of a generalized sample covariance matrix, meaning a matrix proportional to $Z^T \Gamma Z$, where $Z$ has i.i.d. real or complex entries and $\Gamma$ is not necessarily…

Probability · Mathematics 2023-02-07 Jonathan Husson , Benjamin McKenna

We compute the full order statistics of a one-dimensional gas of fermions in a harmonic trap at zero temperature, including its large deviation tails. The problem amounts to computing the probability distribution of the $k$th smallest…

Statistical Mechanics · Physics 2014-11-05 Isaac Pérez Castillo

We prove that for all values of the edge probability p(n) the largest eigenvalue of a random graph G(n,p) satisfies almost surely: \lambda_1(G)=(1+o(1))max{\sqrt{\Delta},np}, where \Delta is a maximal degree of G, and the o(1) term tends to…

Combinatorics · Mathematics 2007-05-23 Michael Krivelevich , Benny Sudakov

This paper centers on the limit eigenvalue distribution for random Vandermonde matrices with unit magnitude complex entries. The phases of the entries are chosen independently and identically distributed from the interval $[-\pi,\pi]$.…

Probability · Mathematics 2015-03-17 Gabriel H. Tucci , Philip A. Whiting

The averages of ratios of characteristic polynomials det(lambda - X) of N x N random matrices X, are investigated in the large N limit for the GUE, GOE and GSE ensemble. The density of states and the two-point correlation function are…

Mathematical Physics · Physics 2009-11-07 E. Brezin , S. Hikami

In this paper, we characterize the asymptotic and large scale behavior of the eigenvalues of wavelet random matrices in high dimensions. We assume that possibly non-Gaussian, finite-variance $p$-variate measurements are made of a…

Statistics Theory · Mathematics 2024-06-11 Patrice Abry , B. Cooper Boniece , Gustavo Didier , Herwig Wendt

One-rank perturbations of Wigner matrices have been closely studied: let $P=\frac{1}{\sqrt{n}}A+\theta vv^T$ with $A=(a_{ij})_{1 \leq i,j \leq n} \in \mathbb{R}^{n \times n}$ symmetric, $(a_{ij})_{1 \leq i \leq j \leq n}$ i.i.d. with…

Probability · Mathematics 2022-08-05 Simona Diaconu

Given a large sample covariance matrix $S_N=\frac 1n\Gamma_N^{1/2}Z_N Z_N^*\Gamma_N^{1/2}\, ,$ where $Z_N$ is a $N\times n$ matrix with i.i.d. centered entries, and $\Gamma_N$ is a $N\times N$ deterministic Hermitian positive semidefinite…

Probability · Mathematics 2021-01-08 Florence Merlevède , Jamal Najim , Peng Tian

We present a large deviation principle at speed N for the largest eigenvalue of some additively deformed Wigner matrices. In particular this includes Gaussian ensembles with full-rank general deformation. For the non-Gaussian ensembles, the…

Probability · Mathematics 2023-03-22 Benjamin McKenna

A fundamental question in random matrix theory is to quantify the optimal rate of convergence to universal laws. We take up this problem for the Laguerre $\beta$ ensemble, characterised by the Dyson parameter $\beta$, and the Laguerre…

Mathematical Physics · Physics 2019-03-26 Peter J. Forrester , Allan K. Trinh

Euclidean random matrices arise in a wide range of physical systems where interactions are determined by spatial configurations, including disordered media and cooperative phenomena in atomic ensembles. Unlike classical random matrix…

Statistical Mechanics · Physics 2026-05-08 Pasquale Casaburi , Pierpaolo Vivo

We define a class of random matrix ensembles that pertain to random looped polymers. Such random looped polymers are a possible model for bio-polymers such as chromatin in the cell nucleus. It is shown that the distribution of the largest…

Statistical Mechanics · Physics 2009-04-16 Dieter W. Heermann , Manfred Bohn

Let $G$ be a $d$-regular graph $G$ on $n$ vertices. Suppose that the adjacency matrix of $G$ is such that the eigenvalue $\lambda$ which is second largest in absolute value satisfies $\lambda=o(d)$. Let $G_p$ with $p=\frac{\alpha}{d}$ be…

Combinatorics · Mathematics 2016-05-25 Alan Frieze , Michael Krivelevich , Ryan R. Martin

The upper tail problem for the largest eigenvalue of the Erd\H{o}s--R\'enyi random graph $\mathcal{G}_{n,p}$ is to estimate the probability that the largest eigenvalue of the adjacency matrix of $\mathcal{G}_{n,p}$ exceeds its typical value…

Probability · Mathematics 2020-12-01 Bhaswar B. Bhattacharya , Shirshendu Ganguly

We present large deviations estimates in the supremum norm for a system of independent random walks superposed with a birth-and-death dynamics evolving on the discrete torus with $N$ sites. The scaling limit considered is the so-called…

Probability · Mathematics 2021-02-26 Tertuliano Franco , Luana A. Gurgel , Bernardo N. B. de Lima

The Airy$_\beta$ point process, $a_i \equiv N^{2/3} (\lambda_i-2)$, describes the eigenvalues $\lambda_i$ at the edge of the Gaussian $\beta$ ensembles of random matrices for large matrix size $N \to \infty$. We study the probability…

Statistical Mechanics · Physics 2019-03-27 Alexandre Krajenbrink , Pierre Le Doussal

Consider a high-dimensional Wishart matrix $\bd{W}=\bd{X}^T\bd{X}$ where the entries of $\bd{X}$ are i.i.d. random variables with mean zero, variance one, and a finite fourth moment $\eta$. Motivated by problems in signal processing and…

Probability · Mathematics 2024-10-22 Tiefeng Jiang , Yongcheng Qi

We evaluate, in the large-$N$ limit, the complete probability distribution $\mathcal{P}(A,m)$ of the values $A$ of the sum $\sum_{i=1}^{N} |\lambda_i|^m$, where $\lambda_i$ ($i=1,2,\dots, N$) are the eigenvalues of a Gaussian random matrix,…

Statistical Mechanics · Physics 2024-02-20 Alexander Valov , Baruch Meerson , Pavel V. Sasorov

Computing the top eigenvectors of a matrix is a problem of fundamental interest to various fields. While the majority of the literature has focused on analyzing the reconstruction error of low-rank matrices associated with the retrieved…

Machine Learning · Computer Science 2022-02-17 Ruo-Chun Tzeng , Po-An Wang , Florian Adriaens , Aristides Gionis , Chi-Jen Lu