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Combined perturbation bounds are presented for eigenvalues and eigenspaces of Hermitian matrices or singular values and singular subspaces of general matrices. The bounds are derived based on the smooth decompositions and elementary…

Numerical Analysis · Mathematics 2025-09-16 Xiao Shan Chen , Hongguo Xu

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

Eigenvalue and eigenvector perturbation theory is a fundamental topic in several disciplines, including numerical linear algebra, quantum physics, and related fields. The central problem is to understand how the eigenvalues and eigenvectors…

Numerical Analysis · Mathematics 2026-02-26 Francesco Hrobat , Yuji Nakatsukasa

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 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

The sensitivity of eigenvalues of structured matrices under general or structured perturbations of the matrix entries has been thoroughly studied in the literature. Error bounds are available and the pseudospectrum can be computed to gain…

Numerical Analysis · Mathematics 2019-04-30 Silvia Noschese , Lothar Reichel

We present first-order perturbation analysis of a simple eigenvalue and the corresponding right and left eigenvectors of a general square matrix, not assumed to be Hermitian or normal. The eigenvalue result is well known to a broad…

Numerical Analysis · Mathematics 2019-06-04 Anne Greenbaum , Ren-cang Li , Michael L. Overton

A defective eigenvalue is well documented to be hypersensitive to data perturbations and round-off? errors, making it a formidable challenge in numerical computation particularly when the matrix is known through approximate data. This paper…

Numerical Analysis · Mathematics 2021-03-05 Zhonggang Zeng

Parameter dependent non-Hermitian quantum systems typically not only possess eigenvalue degeneracies, but also degeneracies of the corresponding eigenfunctions at exceptional points. While the effect of two coalescing eigenfunctions on…

Quantum Physics · Physics 2011-12-21 Gilles Demange , Eva-Maria Graefe

We consider two-point non-self-adjoint boundary eigenvalue problems for linear matrix differential operators. The coefficient matrices in the differential expressions and the matrix boundary conditions are assumed to depend analytically on…

Mathematical Physics · Physics 2010-04-20 Oleg N. Kirillov

In Parts I and II of this series of papers, three new methods for the computation of eigenvalues of singular pencils were developed: rank-completing perturbations, rank-projections, and augmentation. It was observed that a straightforward…

Numerical Analysis · Mathematics 2024-06-12 Michiel E. Hochstenbach , Christian Mehl , Bor Plestenjak

We examine perturbations of eigenvalues and resonances for a class of multi-channel quantum mechanical model-Hamiltonians describing a particle interacting with a localized spin in dimension $d=1,2,3$. We consider unperturbed Hamiltonians…

Mathematical Physics · Physics 2015-05-19 Claudio Cacciapuoti , Raffaele Carlone , Rodolfo Figari

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

Block tridiagonal matrices arise in applied mathematics, physics, and signal processing. Many applications require knowledge of eigenvalues and eigenvectors of block tridiagonal matrices, which can be prohibitively expensive for large…

Spectral Theory · Mathematics 2013-06-04 Aliaksei Sandryhaila , Jose M. F. Moura

This paper offers a review of numerical methods for computation of the eigenvalues of Hermitian matrices and the singular values of general and some classes of structured matrices. The focus is on the main principles behind the methods that…

Numerical Analysis · Mathematics 2020-06-05 Zlatko Drmač

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

Classical matrix perturbation results, such as Weyl's theorem for eigenvalues and the Davis-Kahan theorem for eigenvectors, are general purpose. These classical bounds are tight in the worst case, but in many settings sub-optimal in the…

Machine Learning · Statistics 2017-06-21 Justin Eldridge , Mikhail Belkin , Yusu Wang

We consider the eigenvalues and eigenvectors of finite, low rank perturbations of random matrices. Specifically, we prove almost sure convergence of the extreme eigenvalues and appropriate projections of the corresponding eigenvectors of…

Probability · Mathematics 2012-03-19 Florent Benaych-Georges , Raj Rao Nadakuditi

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

Let $$ A=\left(\begin{array}{cc} H_1 & E^*\\ E & H_2\end{array}\right) \quad \hbox{ and } \quad \wtd A=\left(\begin{array}{cc} H_1 & O\\ O & H_2\end{array}\right)$$ be two $N$-by-$N$ Hermitian matrices with eigenvalues $\lambda_1 \ge \cdots…

Numerical Analysis · Mathematics 2025-08-12 Chi-Kwong Li , Ren-Cang Li
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