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We study ill-conditioned positive definite matrices that are disturbed by the sum of $m$ rank-one matrices of a specific form. We provide estimates for the eigenvalues and eigenvectors. When the condition number of the initial matrix tends…

Numerical Analysis · Mathematics 2024-03-13 Armand Gissler , Anne Auger , Nikolaus Hansen

We consider Gaussian Laplace eigenfunctions on the two-dimensional flat torus (arithmetic random waves), and provide explicit Berry-Esseen bounds in the 1-Wasserstein distance for the normal and non-normal high-energy approximation of the…

Probability · Mathematics 2017-02-14 Giovanni Peccati , Maurizia Rossi

In contrast to the neatly bounded spectra of densely populated large random matrices, sparse random matrices often exhibit unbounded eigenvalue tails on the real and imaginary axis, called Lifshitz tails. In the case of asymmetric matrices,…

Disordered Systems and Neural Networks · Physics 2025-11-07 Pietro Valigi , Joseph W. Baron , Izaak Neri , Giulio Biroli , Chiara Cammarota

For a fixed symmetric matrix A and symmetric perturbation E we develop purely deterministic bounds on how invariant subspaces of A and A+E can differ when measured by a suitable "row-wise" metric rather than via traditional measures of…

Numerical Analysis · Mathematics 2020-06-22 Anil Damle , Yuekai Sun

The discrete spectrum of complex banded matrices which are compact perturbations of the standard banded matrix of order $p$ is under consideration. The rate of stabilization for the matrix entries sharp in the sense of order which provides…

Spectral Theory · Mathematics 2015-06-26 L. Golinskii , M. Kudryavtsev

We consider the Gaussian ensembles of random matrices and describe the normal modes of the eigenvalue spectrum, i.e., the correlated fluctuations of eigenvalues about their most probable values. The associated normal mode spectrum is…

Nuclear Theory · Physics 2009-10-31 A. Andersen , A. D. Jackson , H. J. Pedersen

In this article, we derive concentration inequalities for the spectral norm of two classical sample estimators of large dimensional Toeplitz covariance matrices, demonstrating in particular their asymptotic almost sure consistence. The…

Information Theory · Computer Science 2015-10-28 Julia Vinogradova , Romain Couillet , Walid Hachem

This paper investigates limiting properties of eigenvalues of multivariate sample spatial-sign covariance matrices when both the number of variables and the sample size grow to infinity. The underlying p-variate populations are general…

Statistics Theory · Mathematics 2021-01-25 Weiming Li , Qinwen Wang , Jianfeng Yao , Wang Zhou

There has been much recent interest, initiated by work of the physicists Hatano and Nelson, in the eigenvalues of certain random non-Hermitian periodic tridiagonal matrices and their bidiagonal limits. These eigenvalues cluster along a…

Statistical Mechanics · Physics 2007-05-23 Lloyd N. Trefethen , Marco Contedini , Mark Embree

We develop novel empirical Bernstein inequalities for the variance of bounded random variables. Our inequalities hold under constant conditional variance and mean, without further assumptions like independence or identical distribution of…

Statistics Theory · Mathematics 2026-05-28 Diego Martinez-Taboada , Aaditya Ramdas

Using numerical exact diagonalization, we study matrix elements of a local spin operator in the eigenbasis of two different nonintegrable quantum spin chains. Our emphasis is on the question to what extent local operators can be represented…

Statistical Mechanics · Physics 2020-10-27 Jonas Richter , Anatoly Dymarsky , Robin Steinigeweg , Jochen Gemmer

Patterned random matrices such as the reverse circulant, the symmetric circulant, the Toeplitz and the Hankel matrices and their almost sure limiting spectral distribution (LSD), have attracted much attention. Under the assumption that the…

Probability · Mathematics 2022-03-14 Arup Bose , Koushik Saha , Priyanka Sen

This work provides two results obtained as a consequence of an inversion formula for Toeplitz matrices with real symbol. First we obtain an asymptotic expression for the minimal eigenvalues of a Toeplitz matrix with a symbolwhich is…

Functional Analysis · Mathematics 2017-09-21 Philippe Rambour

Systems with an effectively non-Hermitian Hamiltonian display an enhanced sensitivity to parametric and dynamic perturbations, which arises from the nonorthogonality of their eigenstates. This enhanced sensitivity can be quantified by the…

Quantum Physics · Physics 2023-12-15 Henning Schomerus

Toeplitz matrices have entries that are constant along diagonals. They model directed transport, are at the heart of correlation function calculations of the two-dimensional Ising model, and have applications in quantum information science.…

Mathematical Physics · Physics 2017-05-02 Ramis Movassagh , Leo P. Kadanoff

We prove quadratic eigenvalue perturbation bounds for generalized Hermitian eigenvalue problems. The bounds are proportional to the square of the norm of the perturbation matrices divided by the gap between the spectrums. Using the results…

Numerical Analysis · Mathematics 2010-09-21 Yuji Nakatsukasa

In this paper we study the eigenvalues of Hermitian Toeplitz matrices with the entries $2,-1,0,\ldots,0,-\alpha$ in the first column. Notice that the generating symbol depends on the order $n$ of the matrix. If $|\alpha|\le 1$, then the…

Functional Analysis · Mathematics 2024-01-02 Sergei M. Grudsky , Egor A. Maximenko , Alejandro Soto-González

This article establishes cutoff convergence or abrupt convergence of three statistical quantities for multivariate (Hurwitz) stable geometric Brownian motion: the autocorrelation function, the Wasserstein distance between the current state…

Probability · Mathematics 2025-06-30 G. Barrera , M. A. Högele , J. C. Pardo

Using the diagrammatic method, we derive a set of self-consistent equations that describe eigenvalue distributions of large correlated asymmetric random matrices. The matrix elements can have different variances and be correlated with each…

Disordered Systems and Neural Networks · Physics 2016-12-21 Alexander Kuczala , Tatyana O. Sharpee

This article studies the \emph{robust covariance matrix estimation} of a data collection $X = (x_1,\ldots,x_n)$ with $x_i = \sqrt \tau_i z_i + m$, where $z_i \in \mathbb R^p$ is a \textit{concentrated vector} (e.g., an elliptical random…

Probability · Mathematics 2022-04-12 Cosme Louart , Romain Couillet
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