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The probability of the small deviations of the matrix $AA^T$ determinant is estimated, where $A$ is an $n\times\infty$ random matrix with centered entries having joint Gaussian distribution. The inequality obtained is sharp in a sence.

Probability · Mathematics 2013-03-19 Nadezhda V. Volodko

We compute analytically, for large N, the probability distribution of the number of positive eigenvalues (the index N_{+}) of a random NxN matrix belonging to Gaussian orthogonal (\beta=1), unitary (\beta=2) or symplectic (\beta=4)…

Statistical Mechanics · Physics 2015-05-14 Satya N. Majumdar , Celine Nadal , Antonello Scardicchio , Pierpaolo Vivo

We derive tight lower bounds on the smallest eigenvalue of a sample covariance matrix of a centred isotropic random vector under weak or no assumptions on its components.

Probability · Mathematics 2014-12-17 Pavel Yaskov

We prove two basic conjectures on the distribution of the smallest singular value of random n times n matrices with independent entries. Under minimal moment assumptions, we show that the smallest singular value is of order n^{-1/2}, which…

Probability · Mathematics 2016-12-23 Mark Rudelson , Roman Vershynin

We compute exact asymptotic results for the probability of the occurrence of large deviations of the largest (smallest) eigenvalue of random matrices belonging to the Gaussian orthogonal, unitary and symplectic ensembles. In particular, we…

Statistical Mechanics · Physics 2009-11-13 David S. Dean , Satya N. Majumdar

Let $\sigma_n(\cdot)$ denote the least singular value of a $n \times n$ matrix. It is well-known that $\mathbb{P}[\sigma_n(A) \le \varepsilon] \le \varepsilon n$ if $A$ is drawn from the real Ginibre ensemble of $n \times n$ matrices and…

Probability · Mathematics 2022-06-10 Edward Zeng

In the past 20 years, the study of real eigenvalues of non-symmetric real random matrices has seen important progress. Notwithstanding, central questions still remain open, such as the characterization of their asymptotic statistics and the…

Mathematical Physics · Physics 2016-05-03 Luis Carlos García del Molino , Khashayar Pakdaman , Jonathan Touboul

We obtain a tail bound for the least non-zero singular value of $A-z$ when $A$ is a random matrix and $z$ is an eigenvalue of $A$ in a neighbourhood of a given point $z_0$ in the bulk of the spectrum. The argument relies on a resolvent…

Probability · Mathematics 2024-04-22 Mohammed Osman

This paper investigates the behaviour of the spectrum of generally correlated Gaussian random matrices whose columns are zero-mean independent vectors but have different correlations, under the specific regime where the number of their…

Information Theory · Computer Science 2014-12-30 Abla Kammoun , M. S. Alouini

We study the asymptotic behavior of the eigenvalues of Gaussian perturbations of large Hermitian random matrices for which the limiting eigenvalue density vanishes at a singular interior point or vanishes faster than a square root at a…

Probability · Mathematics 2019-03-27 Tom Claeys , Arno B. J. Kuijlaars , Karl Liechty , Dong Wang

We are interested in two random matrix ensembles related to permutations: the ensemble of permutation matrices following Ewens' distribution of a given parameter $\theta >0$, and its modification where entries equal to $1$ in the matrices…

Probability · Mathematics 2017-11-10 Valentin Bahier

We apply the operation of random independent thinning on the eigenvalues of $n\times n$ Haar distributed unitary random matrices. We study gap probabilities for the thinned eigenvalues, and we study the statistics of the eigenvalues of…

Mathematical Physics · Physics 2017-08-14 Christophe Charlier , Tom Claeys

Let $\bm{x}_1,\cdots,\bm{x}_n$ be a random sample of size $n$ from a $p$-dimensional population distribution, where $p=p(n)\rightarrow\infty$. Consider a symmetric matrix $W=X^\top X$ with parameters $n$ and $p$, where…

Probability · Mathematics 2023-06-16 Jianwei Hu , Seydou Keita , Kang Fu

This paper proves universality of the distribution of the smallest and largest gaps between eigenvalues of generalized Wigner matrices, under some smoothness assumption for the density of the entries. The proof relies on the Erd{\H…

Probability · Mathematics 2020-07-03 Paul Bourgade

The Gaussian and Laguerre orthogonal ensembles are fundamental to random matrix theory, and the marginal eigenvalue distributions are basic observable quantities. Notwithstanding a long history, a formulation providing high precision…

Mathematical Physics · Physics 2024-11-26 Peter J. Forrester , Santosh Kumar , Bo-Jian Shen

We prove lower bounds on the number of samples needed to privately estimate the covariance matrix of a Gaussian distribution. Our bounds match existing upper bounds in the widest known setting of parameters. Our analysis relies on the…

Data Structures and Algorithms · Computer Science 2024-04-30 Victor S. Portella , Nick Harvey

Consider the ensemble of Real Symmetric Toeplitz Matrices, each entry iidrv from a fixed probability distribution p of mean 0, variance 1, and finite higher moments. The limiting spectral measure (the density of normalized eigenvalues)…

Probability · Mathematics 2010-11-16 Christopher Hammond , Steven J. Miller

In this paper we study the limiting distribution of the $k$ smallest gaps between eigenvalues of three kinds of random matrices -- the Ginibre ensemble, the Wishart ensemble and the universal unitary ensemble. All of them follow a…

Probability · Mathematics 2012-07-19 Dai Shi , Yunjiang Jiang

A recent conjecture regarding the average of the minimum eigenvalue of the reduced density matrix of a random complex state is proved. In fact, the full distribution of the minimum eigenvalue is derived exactly for both the cases of a…

Statistical Mechanics · Physics 2009-11-13 Satya N. Majumdar , Oriol Bohigas , Arul Lakshminarayan

We study $n\times n$ random Hermitian matrix ensembles that are invariant under unitary conjugation. Let $I$ be a finite union of intervals lying in the bulk, and let $m_{k}^{(n)}$ be the $k$-th largest gap between consecutive eigenvalues…

Probability · Mathematics 2026-02-24 Christophe Charlier