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This article is devoted to computing the lower and upper bounds of the Laplace eigenvalue problem. By using the special nonconforming finite elements, i.e., enriched Crouzeix-Raviart element and extension $Q_1^{\rm rot}$, we get the lower…

Numerical Analysis · Mathematics 2015-05-30 Fusheng Luo , Qun Lin , Hehu Xie

Recently, three numerical methods for the computation of eigenvalues of singular matrix pencils, based on a rank-completing perturbation, a rank-projection, or an augmentation were developed. We show that all three approaches can be…

Numerical Analysis · Mathematics 2025-02-21 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak

Given the $n\times n$ matrix polynomial $P(x)=\sum_{i=0}^kP_i x^i$, we consider the associated polynomial eigenvalue problem. This problem, viewed in terms of computing the roots of the scalar polynomial $\det P(x)$, is treated in…

Numerical Analysis · Mathematics 2012-07-27 Dario A. Bini , V. Noferini

We develop eigenvalue bounds for symmetric, block tridiagonal multiple saddle-point linear systems, preconditioned with block diagonal matrices. We extend known results for $3 \times 3$ block systems [Bradley and Greif, IMA J.\ Numer. Anal.…

Numerical Analysis · Mathematics 2025-06-04 L. Bergamaschi , A. Martinez , J. W. Pearson , A. Potschka

This paper studies the Schatten-$q$ error of low-rank matrix estimation by singular value decomposition under perturbation. We specifically establish a perturbation bound on the low-rank matrix estimation via a perturbation projection error…

Numerical Analysis · Mathematics 2021-08-16 Yuetian Luo , Rungang Han , Anru R. Zhang

Regularization methods have been recently developed to construct stable approximate solutions to classical partial differential equations considered as final value problems. In this paper, we investigate the backward parabolic problem with…

Analysis of PDEs · Mathematics 2015-10-19 Vo Anh Khoa

Structured perturbation results for invariant subspaces of $\Delta$-Hermitian and Hamiltonian matrices are provided. The invariant subspaces under consideration are associated with the eigenvalues perturbed from a single defective…

Numerical Analysis · Mathematics 2026-01-29 Hongguo Xu

We present a simple, accurate method for solving consistent, rank-deficient linear systems, with or without addi- tional rank-completing constraints. Such problems arise in a variety of applications, such as the computation of the…

Numerical Analysis · Mathematics 2014-01-15 Josef Sifuentes , Zydrunas Gimbutas , Leslie Greengard

A wide range of problems in computational science and engineering require estimation of sparse eigenvectors for high dimensional systems. Here, we propose two variants of the Truncated Orthogonal Iteration to compute multiple leading…

Numerical Analysis · Mathematics 2021-03-26 Hexuan Liu , Aleksandr Aravkin

The structured $\varepsilon$-stability radius is introduced as a quantity to assess the robustness of transient bounds of solutions to linear differential equations under structured perturbations of the matrix. This applies to general…

Numerical Analysis · Mathematics 2024-01-19 Christian Lubich , Nicola Guglielmi

We describe an algorithm to compute the extremal eigenvalues and corresponding eigenvectors of a symmetric matrix by solving a sequence of Quadratic Binary Optimization problems. This algorithm is robust across many different classes of…

Emerging Technologies · Computer Science 2022-10-12 Benjamin Krakoff , Susan M. Mniszewski , Christian F. A. Negre

Recovering low-rank and sparse matrices from incomplete or corrupted observations is an important problem in machine learning, statistics, bioinformatics, computer vision, as well as signal and image processing. In theory, this problem can…

Machine Learning · Computer Science 2014-09-04 Fanhua Shang , Yuanyuan Liu , Hanghang Tong , James Cheng , Hong Cheng

We revisit the relative perturbation theory for invariant subspaces of positive definite matrix pairs. As a prototype model problem for our results we consider parameter dependent families of eigenvalue problems. We show that new estimates…

Numerical Analysis · Mathematics 2010-11-22 Luka Grubišić , Ninoslav Truhar , Krešimir Veselić

The non-Hermitian Bethe-Salpeter eigenvalue problem, in the definite case, is a structured eigenproblem, with real eigenvalues coming in pairs $\{\lambda,-\lambda\}$ where the corresponding pair of eigenvectors are closely related, and…

Numerical Analysis · Mathematics 2026-04-02 Fernando Alvarruiz , Blanca Mellado-Pinto , Jose E. Roman

Quartic eigenvalue problem $(\lambda^4 A + \lambda^3 B + \lambda^2C + \lambda D + E)x = \mathbf{0}$ naturally arises e.g. when solving the Orr-Sommerfeld equation in the analysis of the stability of the {Poiseuille} flow, in theoretical…

Numerical Analysis · Mathematics 2021-03-10 Zlatko Drmač , Ivana Šain Glibić

A thorough backward stability analysis of Hotelling's deflation, an explicit external deflation procedure through low-rank updates for computing many eigenpairs of a symmetric matrix, is presented. Computable upper bounds of the loss of the…

Numerical Analysis · Mathematics 2021-05-05 Chao-Ping Lin , Ding Lu , Zhaojun Bai

The affine inverse eigenvalue problem consists of identifying a real symmetric matrix with a prescribed set of eigenvalues in an affine space. Due to its ubiquity in applications, various instances of the problem have been widely studied in…

Optimization and Control · Mathematics 2019-11-07 Utkan Candogan , Yong Sheng Soh , Venkat Chandrasekaran

We numerically calculate the first few eigenvalues of the perturbations of self-similar solutions of the spherically symmetric co-rotational SU(2) sigma-model on Minkowski space.

Mathematical Physics · Physics 2011-02-18 Roland Donninger , Peter C. Aichelburg

This paper concerns some inverse eigenvalue problems of the quadratic $\star$-(anti)-palindromic system $Q(\lambda)=\lambda^2 A_1^{\star}+\lambda A_0 + \epsilon A_1$, where $\epsilon=\pm 1$, $A_1, A_0 \in \mathbb{C}^{n\times n}$,…

Numerical Analysis · Mathematics 2016-06-14 Yunfeng Cai , Jiang Qian

We provide a computational framework for approximating a class of structured matrices; here, the term structure is very general, and may refer to a regular sparsity pattern (e.g., block-banded), or be more highly structured (e.g., symmetric…

Numerical Analysis · Mathematics 2021-05-05 Misha E. Kilmer , Arvind K. Saibaba
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