English
Related papers

Related papers: Expressing the largest eigenvalue of a singular be…

200 papers

We give the distribution of $M_n$, the maximum of a sequence of $n$ observations from a moving average of order 1. Solutions are first given in terms of repeated integrals and then for the case where the underlying independent random…

Methodology · Statistics 2009-09-07 Christopher S. Withers , Saralees Nadarajah

Let $\mathbf{W}$ be a correlated complex non-central Wishart matrix defined through $\mathbf{W}=\mathbf{X}^H\mathbf{X}$, where $\mathbf{X}$ is $n\times m \, (n\geq m)$ complex Gaussian with non-zero mean $\boldsymbol{\Upsilon}$ and…

Statistics Theory · Mathematics 2015-03-17 Prathapasinghe Dharmawansa , Matthew R. McKay

Let G be a random subgraph of the n-cube where each edge appears randomly and independently with probability p. We prove that the largest eigenvalue of the adjacency matrix of G is almost surely \lambda_1(G)= (1+o(1))…

Probability · Mathematics 2009-11-07 Alexander Soshnikov , Benny Sudakov

In this paper, we study random matrix models which are obtained as a non-commutative polynomial in random matrix variables of two kinds: (a) a first kind which have a discrete spectrum in the limit, (b) a second kind which have a joint…

Probability · Mathematics 2018-09-17 Benoit Collins , Takahiro Hasebe , Noriyoshi Sakuma

The mathematical properties of a family of generalized beta distribution, including beta-normal, skewed-t, log-F, beta-exponential, beta-Weibull distributions have recently been studied in several publications. This paper applies these…

Methodology · Statistics 2007-10-26 J. H. Sepanski , Lingji Kong

We derive concentration inequalities for functions of the empirical measure of large random matrices with infinitely divisible entries and, in particular, stable ones. We also give concentration results for some other functionals of these…

Probability · Mathematics 2007-06-13 Christian Houdré , Hua Xu

Random matrices have played an important role in many fields including machine learning, quantum information theory and optimization. One of the main research focuses is on the deviation inequalities for eigenvalues of random matrices.…

Probability · Mathematics 2018-10-18 Xianjie Gao , Chao Zhang , Hongwei Zhang

Neural networks have been used successfully in a variety of fields, which has led to a great deal of interest in developing a theoretical understanding of how they store the information needed to perform a particular task. We study the…

Disordered Systems and Neural Networks · Physics 2022-11-16 Matthias Thamm , Max Staats , Bernd Rosenow

The large sieve inequality is equivalent to the bound $\lambda_1 \leqslant N + Q^2-1$ for the largest eigenvalue $\lambda_1$ of the $N$ by $N$ matrix $A^{\star} A$, naturally associated to the positive definite quadratic form arising in the…

Number Theory · Mathematics 2018-06-18 Florin P. Boca , Maksym Radziwiłł

In a frequency selective slow-fading channel in a MIMO system, the channel matrix is of the form of a block matrix. This paper proposes a method to calculate the limit of the eigenvalue distribution of block matrices if the size of the…

Information Theory · Computer Science 2011-11-10 Reza Rashidi Far , Tamer Oraby , Wlodzimierz Bryc , Roland Speicher

The article considers an inhomogeneous Erd\H{o}s-R\"enyi random graph on $\{1,\ldots, N\}$, where an edge is placed between vertices $i$ and $j$ with probability $\varepsilon_N f(i/N,j/N)$, for $i\le j$, the choice being made independent…

Probability · Mathematics 2024-02-28 Arijit Chakrabarty , Sukrit Chakraborty , Rajat Subhra Hazra

The sum of independent Wishart matrices, taken from distributions with unequal covariance matrices, plays a crucial role in multivariate statistics, and has applications in the fields of quantitative finance and telecommunication. However,…

Mathematical Physics · Physics 2014-09-23 Santosh Kumar

Non-Hermitian random matrices with statistical spectral characteristics beyond the standard Ginibre ensembles have recently emerged in the description of dissipative quantum many-body systems as well as in non-ergodic wave transport in…

Mathematical Physics · Physics 2025-11-27 Gernot Akemann , Yan V. Fyodorov , Dmitry V. Savin

Eigenvalue distributions are important dynamical quantities in matrix models, and it is an interesting challenge to study corresponding quantities in tensor models. We study real tensor eigenvalue/vector distributions for real symmetric…

High Energy Physics - Theory · Physics 2022-12-16 Naoki Sasakura

The gamma difference distribution is defined as the difference of two gamma distributions, with in general different shape and rate parameters. Starting with knowledge of the corresponding characteristic function, a second order linear…

Statistics Theory · Mathematics 2023-09-26 Peter J. Forrester

Let $X,X_1,\ldots,X_n$ be independent identically distributed random variables. The paper deals with the question about the behavior of the concentration function of the random variable $\sum\limits_{k=1}^{n}X_k a_k$ according to the…

Probability · Mathematics 2013-03-19 Yu. S. Eliseeva

The distribution of singular values of the propagation operator in a random medium is investigated, in a backscattering configuration. Experiments are carried out with pulsed ultrasonic waves around 3 MHz, using an array of 64 programmable…

Classical Physics · Physics 2010-07-20 Alexandre Aubry , Arnaud Derode

Dirac operator eigenvalues split into two when subjected to two different external vector sources. In a specific finite-volume scaling regime of gauge theories with fermions, this problem can be mapped to a chiral Random Two-Matrix Theory.…

High Energy Physics - Theory · Physics 2014-11-18 G. Akemann , P. H. Damgaard

The distribution function for the first eigenvalue spacing in the Laguerre unitary ensemble of finite rank random matrices is found in terms of a Painlev\'e V system, and the solution of its associated linear isomonodromic system. In…

Classical Analysis and ODEs · Mathematics 2007-07-12 Peter J. Forrester , Nicholas S. Witte

This work analyzes singular-value spectra of weight matrices in pretrained transformer models to understand how information is stored at both ends of the spectrum. Using Random Matrix Theory (RMT) as a zero information hypothesis, we…

Machine Learning · Computer Science 2025-11-07 Max Staats , Matthias Thamm , Bernd Rosenow