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Random matrix theory allows one to deduce the eigenvalue spectrum of a large matrix given only statistical information about its elements. Such results provide insight into what factors contribute to the stability of complex dynamical…

Disordered Systems and Neural Networks · Physics 2025-01-30 Joseph W. Baron , Thomas Jun Jewell , Christopher Ryder , Tobias Galla

This paper is concerned with the interplay between statistical asymmetry and spectral methods. Suppose we are interested in estimating a rank-1 and symmetric matrix $\mathbf{M}^{\star}\in \mathbb{R}^{n\times n}$, yet only a randomly…

Statistics Theory · Mathematics 2023-01-10 Yuxin Chen , Chen Cheng , Jianqing Fan

Computing the first few singular vectors of a large matrix is a problem that frequently comes up in statistics and numerical analysis. Given the presence of noise, exact calculation is hard to achieve, and the following problem is of…

Numerical Analysis · Mathematics 2010-04-13 Van Vu

Generalized eigenvalue problems involving a singular pencil may be very challenging to solve, both with respect to accuracy and efficiency. While Part I presented a rank-completing addition to a singular pencil, we now develop two…

Numerical Analysis · Mathematics 2023-10-26 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak

In [M. Walter et al., Science 340, 1205, 7 June (2013)], they gave a sufficient condition for genuinely entangled pure states and discussed SLOCC classification via polytopes and the eigenvalues of the single-particle states. In this paper,…

Quantum Physics · Physics 2019-12-05 Dafa Li

A new approach to solving eigenvalue optimization problems for large structured matrices is proposed and studied. The class of optimization problems considered is related to computing structured pseudospectra and their extremal points, and…

Numerical Analysis · Mathematics 2022-06-22 Nicola Guglielmi , Christian Lubich , Stefano Sicilia

This article deals with the spectra of Laplacians of weighted graphs. In this context, two objects are of fundamental importance for the dynamics of complex networks: the second eigenvalue of such a spectrum (called algebraic connectivity)…

Mathematical Physics · Physics 2017-04-07 Camille Poignard , Tiago Pereira , Jan Philipp Pade

For generic values of q, all the eigenvectors of the transfer matrix of the U_q sl(2)-invariant open spin-1/2 XXZ chain with finite length N can be constructed using the algebraic Bethe ansatz (ABA) formalism of Sklyanin. However, when q is…

Mathematical Physics · Physics 2017-05-24 Azat M. Gainutdinov , Rafael I. Nepomechie

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

The diagonalization of matrices may be the top priority in the application of modern physics. In this paper, we numerically demonstrate that, for real symmetric random matrices with non-positive off-diagonal elements, a universal scaling…

Quantum Physics · Physics 2020-11-06 Wei Pan , Jing Wang , Deyan Sun

In this paper, we study spectral properties of generalized weighted Hilbert matrices. In particular, we establish results on the spectral norm, determinant, as well as various relations between the eigenvalues and eigenvectors of such…

Spectral Theory · Mathematics 2013-03-06 Emmanuel Preissmann , Olivier Leveque

This paper investigates the critical role of eigenalignments between the kernel matrix and learning targets in achieving robust generalization in learning problems. We establish a direct connection between generalization performance in…

Machine Learning · Statistics 2026-05-18 Yang Liu , Ernest Fokoue , Richard Lange , Daniel Krutz

In many applications it is important to understand the sensitivity of eigenvalues of a matrix polynomial to perturbations of the polynomial. The sensitivity commonly is described by condition numbers or pseudospectra. However, the…

Numerical Analysis · Mathematics 2017-04-06 Silvia Noschese , Lothar Reichel

The eigenvalues and eigenvectors of nonnormal matrices can be unstable under perturbations of their entries. This renders an obstacle to the analysis of numerical algorithms for non-Hermitian eigenvalue problems. A recent technique to…

Probability · Mathematics 2026-04-14 Rikhav Shah , Nikhil Srivastava , Edward Zeng

Let $k$ be a field and $n,a,b$ natural numbers. A matrix pencil $P$ is given by $n$ matrices of the same size with coefficients in $k$, say by $(b\times a)$-matrices, or, equivalently, by $n$ linear transformations $\alpha_i\:k^a \to k^b$…

Numerical Analysis · Mathematics 2017-05-02 Claus Michael Ringel

We propose a general framework to study the stability of the subspace spanned by $P$ consecutive eigenvectors of a generic symmetric matrix ${\bf H}_0$, when a small perturbation is added. This problem is relevant in various contexts,…

Statistical Mechanics · Physics 2013-01-29 Romain Allez , Jean-Philippe Bouchaud

For piecewise expanding one-dimensional maps without periodic turning points we prove that isolated eigenvalues of small (random) perturbations of these maps are close to isolated eigenvalues of the unperturbed system. (Here ``eigenvalue''…

chao-dyn · Physics 2009-10-30 Michael Blank , Gerhard Keller

This paper is a didactic commentary (a transcription with variations) to the paper of S.R. Foguel {\it Finite Dimensional Perturbations in Banach Spaces}. Addressed, mainly: postgraduates and related readers. Subject: Suppose we have two…

Mathematical Physics · Physics 2016-09-07 Sergej A. Choroszavin

A theory of rank $k\ge 2$ perturbation of symplectic matrices and Hamiltonian systems with periodic coefficients using a base of isotropic subspaces, is presented. After showing that the fundamental matrix ${\displaystyle…

Numerical Analysis · Mathematics 2017-12-12 Traoré G. Y. Arouna , Mouhamadou Dosso , Jean-Claude Koua Brou

Quantifying the eigenvalue spectra of large random matrices allows one to understand the factors that contribute to the stability of dynamical systems with many interacting components. This work explores the effect that the interaction…

Disordered Systems and Neural Networks · Physics 2022-12-08 Joseph W. Baron
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