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For compact self-adjoint operators in Hilbert spaces, two algorithms are proposed to provide fully computable a posteriori error estimate for eigenfunction approximation. Both algorithms apply well to the case of tight clusters and multiple…

Numerical Analysis · Mathematics 2022-07-19 Xuefeng Liu , Tomáš Vejchodský

We investigate how invariant subspaces corresponding to a single eigenvalue will change when a matrix is perturbed. We focus on the invariant subspaces corresponding to an eigenvalue associated with the Jordan blocks that have the same…

Numerical Analysis · Mathematics 2024-09-24 Hongguo Xu

This work is concerned with approximating the smallest eigenvalue of a parameter-dependent Hermitian matrix $A(\mu)$ for many parameter values $\mu \in \mathbb{R}^P$. The design of reliable and efficient algorithms for addressing this task…

Numerical Analysis · Mathematics 2015-04-24 Petar Sirković , Daniel Kressner

Random matrix theory has become a widely useful tool in high-dimensional statistics and theoretical machine learning. However, random matrix theory is largely focused on the proportional asymptotics in which the number of columns grows…

Statistics Theory · Mathematics 2025-06-23 Chen Cheng , Andrea Montanari

This work introduces the minimax Laplace transform method, a modification of the cumulant-based matrix Laplace transform method developed in "User-friendly tail bounds for sums of random matrices" (arXiv:1004.4389v6) that yields both upper…

Probability · Mathematics 2011-07-22 Alex Gittens , Joel A. Tropp

We consider Hermitian random band matrices $H=(h_{xy})$ on the $d$-dimensional lattice $(\mathbb Z/L\mathbb Z)^d$. The entries $h_{xy}$ are independent (up to Hermitian conditions) centered complex Gaussian random variables with variances…

Probability · Mathematics 2021-07-15 Fan Yang , Horng-Tzer Yau , Jun Yin

Besides perturbation theory, which requires, of course, the knowledge of the exact unperturbed solution, variational techniques represent the main tool for any investigation of the eigenvalue problem of some semibounded operator H in…

High Energy Physics - Phenomenology · Physics 2016-12-28 Wolfgang Lucha , F. F. Schoberl

Many popular eigensolvers for large and sparse Hermitian matrices or matrix pairs can be interpreted as accelerated block preconditioned gradient (BPG) iterations in order to analyze their convergence behavior by composing known estimates.…

Numerical Analysis · Mathematics 2022-06-02 Ming Zhou , Klaus Neymeyr

Normalized eigenvalue counting measure of the sum of two Hermitian (or real symmetric) matrices $A_{n}$ and $B_{n}$ rotated independently with respect to each other by the random unitary (or orthogonal) Haar distributed matrix $U_{n}$ (i.e.…

Mathematical Physics · Physics 2016-08-15 L. Pastur , V. Vasilchuk

Improving upon results of Rudelson and Vershynin, we establish delocalization bounds for eigenvectors of independent-entry random matrices. In particular, we show that with high probability every eigenvector is delocalized, meaning any…

Probability · Mathematics 2019-02-01 Kyle Luh , Sean O'Rourke

Pseudo-hermitian matrices are matrices hermitian with respect to an indefinite metric. They can be thought of as the truncation of pseudo-hermitian operators, defined over some Krein space, together with the associated metric, to a finite…

Mathematical Physics · Physics 2022-02-03 Joshua Feinberg , Roman Riser

Sylvester's law of inertia states that the number of positive, negative and zero eigenvalues of Hermitian matrices is preserved under congruence transformations. The same is true of generalized Hermitian definite eigenvalue problems, in…

Numerical Analysis · Mathematics 2017-11-03 Yuji Nakatsukasa , Vanni Noferini

We study Hermitian random matrix models with an external source matrix which has equispaced eigenvalues, and with an external field such that the limiting mean density of eigenvalues is supported on a single interval as the dimension tends…

Mathematical Physics · Physics 2013-06-25 Tom Claeys , Dong Wang

The worst situation in computing the minimal nonnegative solution of a nonsymmetric algebraic Riccati equation associated with an M-matrix occurs when the corresponding linearizing matrix has two very small eigenvalues, one with positive…

Numerical Analysis · Mathematics 2014-08-26 Bruno Iannazzo , Federico Poloni

We prove localization with high probability on sets of size of order $N/\log N$ for the eigenvectors of non-Hermitian finitely banded $N\times N$ Toeplitz matrices $P_N$ subject to small random perturbations, in a very general setting. As…

Spectral Theory · Mathematics 2023-08-02 Anirban Basak , Martin Vogel , Ofer Zeitouni

Consider the problem of solving systems of linear algebraic equations $Ax=b$ with a real symmetric positive definite matrix $A$ using the conjugate gradient (CG) method. To stop the algorithm at the appropriate moment, it is important to…

Numerical Analysis · Mathematics 2023-02-27 Gérard Meurant , Petr Tichý

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

This work is concerned with finite range bounds on the variance of individual eigenvalues of Wigner random matrices, in the bulk and at the edge of the spectrum, as well as for some intermediate eigenvalues. Relying on the GUE example,…

Probability · Mathematics 2012-07-06 Sandrine Dallaporta

In this paper, we derive new relative perturbation bounds for eigenvectors and eigenvalues for regular quadratic eigenvalue problems of the form $\lambda^2 M x + \lambda C x + K x = 0$, where $M$ and $K$ are nonsingular Hermitian matrices…

Numerical Analysis · Mathematics 2021-04-02 Peter Benner , Xin Liang , Suzana Miodragović , Ninoslav Truhar

In this paper, we study the deep Ritz method for solving the linear elasticity equation from a numerical analysis perspective. A modified Ritz formulation using the $H^{1/2}(\Gamma_D)$ norm is introduced and analyzed for linear elasticity…

Numerical Analysis · Mathematics 2023-08-02 Min Liu , Zhiqiang Cai , Karthik Ramani