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We study the gaps between consecutive singular values of random rectangular matrices. Specifically, if $M$ is an $n \times p$ random matrix with independent and identically distributed entries and $\Sigma$ is a $n \times n$ deterministic…

Probability · Mathematics 2025-10-07 Nicholas Christoffersen , Kyle Luh , Sean O'Rourke , Calum Shearer

Let $\mathbb{A}_p=\frac{\mathbb{Y}\mathbb{Y}^*}{m}$ and $\mathbb{B}_p=\frac{\mathbb{X}\mathbb{X}^*}{n}$ be two independent random matrices where $\mathbb{X}=(X_{ij})_{p \times n}$ and $\mathbb{Y}=(Y_{ij})_{p \times m}$ respectively consist…

Statistics Theory · Mathematics 2015-06-02 X. Han , G. M. Pan , B. Zhang

In this paper, we consider the singular values and singular vectors of finite, low rank perturbations of large rectangular random matrices. Specifically, we prove almost sure convergence of the extreme singular values and appropriate…

Probability · Mathematics 2012-01-27 Florent Benaych-Georges , Raj Rao Nadakuditi

We study Fredholm determinants of the Painlev\'e II and Painlev\'e XXXIV kernels. In certain critical unitary random matrix ensembles, these determinants describe special gap probabilities of eigenvalues. We obtain Tracy-Widom formulas for…

Mathematical Physics · Physics 2018-09-26 Shuai-Xia Xu , Dan Dai

We study the distribution of the largest eigenvalue in formal Hermitian one-matrix models at multicriticality, where the spectral density acquires an extra number of k-1 zeros at the edge. The distributions are directly expressed through…

Mathematical Physics · Physics 2012-12-18 Gernot Akemann , Max R. Atkin

A method based on multicanonical Monte Carlo is applied to the calculation of large deviations in the largest eigenvalue of random matrices. The method is successfully tested with the Gaussian orthogonal ensemble (GOE), sparse random…

Statistical Mechanics · Physics 2013-05-29 Nen Saito , Yukito Iba , Koji Hukushima

For a pair of coupled rectangular random matrices we consider the squared singular values of their product, which form a determinantal point process. We show that the limiting mean distribution of these squared singular values is described…

Mathematical Physics · Physics 2020-06-24 Guilherme L. F. Silva , Lun Zhang

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

Given two positive integers $n$ and $k$ and a parameter $t\in (0,1)$, we choose at random a vector subspace $V_{n}\subset \mathbb{C}^{k}\otimes\mathbb{C}^{n}$ of dimension $N\sim tnk$. We show that the set of $k$-tuples of singular values…

Probability · Mathematics 2015-05-19 S. Belinschi , B. Collins , I. Nechita

Wishart random matrices with a sparse or diluted structure are ubiquitous in the processing of large datasets, with applications in physics, biology and economy. In this work we develop a theory for the eigenvalue fluctuations of diluted…

Disordered Systems and Neural Networks · Physics 2018-03-20 Isaac Pérez Castillo , Fernando L. Metz

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

This paper investigates a statistical procedure for testing the equality of two independent estimated covariance matrices when the number of potentially dependent data vectors is large and proportional to the size of the vectors, that is,…

Statistics Theory · Mathematics 2020-03-09 Rémy Mariétan , Stephan Morgenthaler

We study two types of random matrix ensembles that emerge when considering the same probability measure on partitions. One is the Meixner ensemble with a hard wall and the other are two families of unitary matrix models, with weight…

Mathematical Physics · Physics 2020-09-09 Leonardo Santilli , Miguel Tierz

These expository notes are centered around the circular law theorem, which states that the empirical spectral distribution of a nxn random matrix with i.i.d. entries of variance 1/n tends to the uniform law on the unit disc of the complex…

Probability · Mathematics 2012-03-14 Charles Bordenave , Djalil Chafai

Asymptotic behavior of the singular value decomposition (SVD) of blown up matrices and normalized blown up contingency tables exposed to Wigner-noise is investigated.It is proved that such an m\times n matrix almost surely has a constant…

Probability · Mathematics 2010-01-11 Marianna Bolla , Katalin Friedl , Andras Kramli

Various ensembles of random matrices with independent entries are analyzed by the replica formalism in the large-N limit. A result on the Laplacian random matrix with Wigner-rescaling is generalized to arbitrary probability distribution.

Statistical Mechanics · Physics 2009-11-11 Giovanni M. Cicuta , Henri Orland

The largest eigenvalue of random tensors is an important feature of systems involving disorder, equivalent to the ground state energy of glassy systems or to the injective norm of quantum states. For symmetric Gaussian random tensors of…

High Energy Physics - Theory · Physics 2024-12-16 Nicolas Delporte , Naoki Sasakura

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

Detection of the number of signals corrupted by high-dimensional noise is a fundamental problem in signal processing and statistics. This paper focuses on a general setting where the high-dimensional noise has an unknown complicated…

Statistics Theory · Mathematics 2022-05-16 Xiucai Ding , Fan Yang

This article carries out a large dimensional analysis of standard regularized discriminant analysis classifiers designed on the assumption that data arise from a Gaussian mixture model with different means and covariances. The analysis…

Machine Learning · Statistics 2019-06-19 Khalil Elkhalil , Abla Kammoun , Romain Couillet , Tareq Y. Al-Naffouri , Mohamed-Slim Alouini