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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

We study large Wigner random matrices in the case when the marginal distributions of matrix entries have heavy tails. We prove that the largest eigenvalues of such matrices have Poisson statistics.

Probability · Mathematics 2007-05-23 Alexander Soshnikov

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

We prove that with high probability, every eigenvector of a random matrix is delocalized in the sense that any subset of its coordinates carries a non-negligible portion of its $\ell_2$ norm. Our results pertain to a wide class of random…

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

We introduce a new random matrix model called distance covariance matrix in this paper, whose normalized trace is equivalent to the distance covariance. We first derive a deterministic limit for the eigenvalue distribution of the distance…

Statistics Theory · Mathematics 2021-05-18 Weiming Li , Qinwen Wang , Jianfeng Yao

This paper studies the delocalized regime of an ultrametric random operator whose independent entries have variances decaying in a suitable hierarchical metric on $\mathbb{N}$. When the decay-rate of the off-diagonal variances is…

Mathematical Physics · Physics 2019-08-28 Per von Soosten , Simone Warzel

The spectrum of the nonbacktracking matrix associated to a network is known to contain fundamental information regarding percolation properties of the network. Indeed, the inverse of its leading eigenvalue is often used as an estimate for…

Physics and Society · Physics 2025-01-30 James Martin , Tim Rogers , Luca Zanetti

Given a large, high-dimensional sample from a spiked population, the top sample covariance eigenvalue is known to exhibit a phase transition. We show that the largest eigenvalues have asymptotic distributions near the phase transition in…

Probability · Mathematics 2013-07-24 Alex Bloemendal , Bálint Virág

In this work we consider deterministic, symmetric matrices with heavy-tailed noise imposed on entries within a fixed distance $K$ to the diagonal. The most important example is discrete 1d random Schr\"odinger operator defined on…

Probability · Mathematics 2025-07-01 Yi Han

Eigenvector localization refers to the situation when most of the components of an eigenvector are zero or near-zero. This phenomenon has been observed on eigenvectors associated with extremal eigenvalues, and in many of those cases it can…

Discrete Mathematics · Computer Science 2011-09-08 Mihai Cucuringu , Michael W. Mahoney

The paper studies the spectral properties of large Wigner, band and sample covariance random matrices with heavy tails of the marginal distributions of matrix entries.

Probability · Mathematics 2015-06-26 Alexander Soshnikov

We analyze random walks on a class of semigroups called ``left-regular bands''. These walks include the hyperplane chamber walks of Bidigare, Hanlon, and Rockmore. Using methods of ring theory, we show that the transition matrices are…

Probability · Mathematics 2007-05-23 Kenneth S. Brown

We study the asymptotic distribution of the eigenvalues of random Hermitian periodic band matrices, focusing on the spectral edges. The eigenvalues close to the edges converge in distribution to the Airy point process if (and only if) the…

Mathematical Physics · Physics 2011-01-25 Sasha Sodin

We study two-banded, non-Hermitian random matrices inspired by sparse neural networks with a circular, 1d topology. We focus on two paradigmatic models, an SSH chain and a ladder model, which have both non-Hermitian directional bias and…

Disordered Systems and Neural Networks · Physics 2026-05-20 Richard Huang , David R. Nelson

We study the joint limit distribution of the $k$ largest eigenvalues of a $p\times p$ sample covariance matrix $XX^\T$ based on a large $p\times n$ matrix $X$. The rows of $X$ are given by independent copies of a linear process,…

Probability · Mathematics 2012-10-31 Richard A. Davis , Oliver Pfaffel , Robert Stelzer

We extend classical time-frequency limiting analysis, historically applied to one-dimensional finite signals, to the multidimensional discrete setting. This extension is relevant for images, videos, and other multidimensional signals, as it…

Classical Analysis and ODEs · Mathematics 2025-07-15 Luis Gomez , Jonathan Jaimangal , Azita Mayeli , Tasfia Proma

In this paper we study the joint distributional convergence of the largest eigenvalues of the sample covariance matrix of a $p$-dimensional time series with iid entries when $p$ converges to infinity together with the sample size $n$. We…

Probability · Mathematics 2016-08-26 Johannes Heiny , Thomas Mikosch

We study a class of Gaussian random band matrices of dimension $N \times N$ and band-width $W$. We show that delocalization holds for bulk eigenvectors and that quantum diffusion holds for the resolvent, all under the assumption that $W \gg…

Probability · Mathematics 2024-12-20 Sofiia Dubova , Kevin Yang

We study the probability distribution function $P(\lambda)$ of the largest eigenvalue $\lambda_{\rm max}$ of $N \times N$ random matrices of the form $H + V$, where $H$ belongs to the GOE/GUE ensemble and $V$ is a full rank deterministic…

Statistical Mechanics · Physics 2025-10-14 Pierre Le Doussal

The level-spacing distribution in the tails of the eigenvalue bands of the power-law random banded matrix (PRBM) ensemble have been investigated numerically. The change of level-spacing statistics across the band is examined for different…

Mesoscale and Nanoscale Physics · Physics 2009-11-11 C. J. Paley , S. N. Taraskin , S. R. Elliott