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We study the fluctuations associated to the a.s. convergence, established by Belinschi-Bercovici-Capitaine, of the outliers of an Hermitian polynomial in a complex Wigner matrix and a spiked deterministic real diagonal matrix. Thus, we…

Probability · Mathematics 2019-06-06 Mireille Capitaine

We study the distribution of the outliers in the spectrum of finite rank deformations of Wigner random matrices. We assume that the matrix entries have finite fourth moment and extend the results by Capitaine, Donati-Martin, and F\'eral for…

Probability · Mathematics 2012-10-24 David Renfrew , Alexander Soshnikov

The spectral form factor of random matrix theory plays a key role in the description of disordered and chaotic quantum systems. While its moments are known to be approximately Gaussian, corrections subleading in the matrix dimension, $D$,…

Quantum Physics · Physics 2026-01-06 Alex Altland , Francisco Divi , Tobias Micklitz , Silvia Pappalardi , Maedeh Rezaei

We analyze the spectral properties of the high-dimensional random geometric graph $G(n, d, p)$, formed by sampling $n$ i.i.d vectors $\{v_i\}_{i=1}^{n}$ uniformly on a $d$-dimensional unit sphere and connecting each pair $\{i,j\}$ whenever…

Probability · Mathematics 2026-02-11 Yifan Cao , Yizhe Zhu

In this paper we study random matrix models where the matrices in question contain infinitely many spikes. Recent work has characterized the possible outliers in the spectrum of large deformed unitarily invariant models when the number of…

Probability · Mathematics 2019-04-03 Brady Thompson

Here we introduce the non-Hermitian diluted banded random matrix (nHdBRM) ensemble as the set of $N\times N$ real non-symmetric matrices whose entries are independent Gaussian random variables with zero mean and variance one if $|i-j|<b$…

Disordered Systems and Neural Networks · Physics 2024-06-25 M. Hernández-Sánchez , G. Tapia-Labra , J. A. Mendez-Bermudez

We present a new approach, based on graphon theory, to finding the limiting spectral distributions of general Wigner-type matrices. This approach determines the moments of the limiting measures and the equations of their Stieltjes…

Probability · Mathematics 2020-08-11 Yizhe Zhu

We consider a square random matrix of size N of the form A + Y where A is deterministic and Y has iid entries with variance 1/N. Under mild assumptions, as N grows, the empirical distribution of the eigenvalues of A+Y converges weakly to a…

Probability · Mathematics 2014-11-04 Charles Bordenave , Mireille Capitaine

In this work we study symmetric random matrices with variance profile satisfying certain conditions. We establish the convergence of the operator norm of these matrices to the largest element of the support of the limiting empirical…

Probability · Mathematics 2024-04-23 Dimitris Cheliotis , Michail Louvaris

We study the deviation inequality for the spectral norm of structured random matrices with non-gaussian entries. In particular, we establish an optimal bound for the $p$-th moment of the spectral norm by transfering the spectral norm into…

Probability · Mathematics 2024-05-14 Guozheng Dai , Zhonggen Su

This paper aims to examine the characteristics of the posterior distribution of covariance/precision matrices in a "large $p$, large $n$" scenario, where $p$ represents the number of variables and $n$ is the sample size. Our analysis…

Statistics Theory · Mathematics 2026-02-02 Partha Sarkar , Kshitij Khare , Malay Ghosh , Matt P. Wand

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

Spike-and-slab and horseshoe regression are arguably the most popular Bayesian variable selection approaches for linear regression models. However, their performance can deteriorate if outliers and heteroskedasticity are present in the…

Methodology · Statistics 2022-10-20 Alberto Cabezas , Marco Battiston , Christopher Nemeth

We discuss the inhomogeneous spiked Wigner model, a theoretical framework recently introduced to study structured noise in various learning scenarios, through the prism of random matrix theory, with a specific focus on its spectral…

Machine Learning · Statistics 2024-09-06 Pierre Mergny , Justin Ko , Florent Krzakala

We derive the joint asymptotic distribution of the outlier eigenvalues of an additively deformed Wigner matrix $H$. Our only assumptions on the deformation are that its rank be fixed and its norm bounded. Our results extend those of [The…

Probability · Mathematics 2014-09-04 Antti Knowles , Jun Yin

We investigate the asymptotic behavior of the eigenvalues of spiked perturbations of Wigner matrices when the dimension goes to infinity. The entries of the Hermitian Wigner matrix have a distribution which is symmetric and satisfies a…

Probability · Mathematics 2011-09-19 Mireille Capitaine , Catherine Donati-Martin , Delphine Féral , Maxime Février

We study the statistical and dynamic properties of the systems characterized by an ultrametric space of states and translationary non-invariant symmetric transition matrices of the Parisi type subjected to "locally constant" randomization.…

Disordered Systems and Neural Networks · Physics 2009-11-13 V. A. Avetisov , A. Kh. Bikulov , S. K. Nechaev

In this article we study the fluctuation of linear statistics of eigenvalues of circulant, symmetric circulant, reverse circulant and Hankel matrices. We show that the linear spectral statistics of these matrices converges to the Gaussian…

Probability · Mathematics 2017-07-05 Kartick Adhikari , Koushik Saha

In this text, based on elementary computations, we provide a perturbative expansion of the coordinates of the eigenvectors of a Hermitian matrix of large size perturbed by a random matrix with small operator norm whose entries in the…

Probability · Mathematics 2020-03-19 Florent Benaych-Georges , Nathanaël Enriquez , Alkéos Michaïl

We consider a class of sparse random matrices, which includes the adjacency matrix of Erd\H{o}s-R\'enyi graphs $\mathcal G(N,p)$ for $p \in [N^{\varepsilon-1},N^{-\varepsilon}]$. We identify the joint limiting distributions of the…

Probability · Mathematics 2020-03-13 Yukun He