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We present a new algorithm for solving an eigenvalue problem for a real symmetric matrix which is a rank-one modification of a diagonal matrix. The algorithm computes each eigenvalue and all components of the corresponding eigenvector with…

Numerical Analysis · Mathematics 2015-09-22 Nevena Jakovcevic Stor , Ivan Slapnicar , Jesse L. Barlow

We introduce a backward stable algorithm for computing the CS decomposition of a partitioned $2n \times n$ matrix with orthonormal columns, or a rank-deficient partial isometry. The algorithm computes two $n \times n$ polar decompositions…

Numerical Analysis · Mathematics 2018-04-25 Evan S. Gawlik , Yuji Nakatsukasa , Brian D. Sutton

Solving large-scale eigenvalue problems poses a significant challenge due to the computational complexity and limitations on the parallel scalability of the orthogonalization operation, when many eigenpairs are required. In this paper, we…

Numerical Analysis · Mathematics 2025-11-11 Tianyang Chu , Xiaoying Dai , Shengyue Wang , Aihui Zhou

We consider eigenvalue condition numbers and backward errors for a class of symmetric nonlinear eigenvalue problems with eigenvector nonlinearities. For both of these quantities, we derive explicit and computable expressions that can be…

Numerical Analysis · Mathematics 2026-05-21 Vilhelm Peterson Lithell , Victor Janssens , Elias Jarlebring , Karl Meerbergen , Wim Michiels

In this paper, we discuss numerical methods for the eigenvalue decomposition of real symmetric matrices. While many existing methods can compute approximate eigenpairs with sufficiently small backward errors, the magnitude of the resulting…

Numerical Analysis · Mathematics 2026-02-24 Takeshi Terao , Katsuhisa Ozaki

Deflation techniques are typically used to shift isolated clusters of small eigenvalues in order to obtain a tighter distribution and a smaller condition number. Such changes induce a positive effect in the convergence behavior of Krylov…

Numerical Analysis · Mathematics 2024-05-15 Andrei Dumitrasc , Carola Kruse , Ulrich Ruede

This paper studies the deflation algorithm when applied to estimate a low-rank symmetric spike contained in a large tensor corrupted by additive Gaussian noise. Specifically, we provide a precise characterization of the large-dimensional…

Machine Learning · Statistics 2023-04-21 Mohamed El Amine Seddik , José Henrique de Morais Goulart , Maxime Guillaud

For a quadratic matrix polynomial associated with a damped mass-spring system there are three types of critical eigenvalues, the eigenvalues $\infty$ and $0$ and the eigenvalues on the imaginary axis. All these are on the boundary of the…

Numerical Analysis · Mathematics 2025-07-23 Rafikul Alam , Volker Mehrmann , Ninoslav Truhar

Snapshot matrices built from solutions to hyperbolic partial differential equations exhibit slow decay in singular values, whereas fast decay is crucial for the success of projection- based model reduction methods. To overcome this problem,…

Numerical Analysis · Mathematics 2017-01-27 Donsub Rim , Scott Moe , Randall J. LeVeque

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

This paper is concerned with computations of a few smaller eigenvalues (in absolute value) of a large extremely ill-conditioned matrix. It is shown that smaller eigenvalues can be accurately computed for a diagonally dominant matrix or a…

Numerical Analysis · Mathematics 2017-05-16 Qiang Ye

Multiple equilibrium states arise in many physical systems, including various types of liquid crystal structures. Having the ability to reliably compute such states enables more accurate physical analysis and understanding of experimental…

Numerical Analysis · Mathematics 2016-01-28 J. H. Adler , D. B. Emerson , P. E. Farrell , S. P. MacLachlan

We study the stability of the Lanczos algorithm run on problems whose eigenvector empirical spectral distribution is near to a reference measure with well-behaved orthogonal polynomials. We give a backwards stability result which can be…

Numerical Analysis · Mathematics 2024-05-14 Tyler Chen , Thomas Trogdon

We present a new algorithm for solving an eigenvalue problem for a real symmetric arrowhead matrix. The algorithm computes all eigenvalues and all components of the corresponding eigenvectors with high relative accuracy in $O(n^{2})$…

Numerical Analysis · Mathematics 2014-05-30 Nevena Jakovcevic Stor , Ivan Slapnicar , Jesse L. Barlow

Computing the trace of the inverse of large matrices is typically addressed through statistical methods. Deflating out the lowest eigenvectors or singular vectors of the matrix reduces the variance of the trace estimator. This work…

Numerical Analysis · Mathematics 2020-03-18 Eloy Romero , Andreas Stathopoulos , Kostas Orginos

This paper presents the forward and backward derivatives of partial eigendecomposition, i.e. where it only obtains some of the eigenpairs, of a real symmetric matrix for degenerate cases. The numerical calculation of forward and backward…

Numerical Analysis · Mathematics 2020-11-10 Muhammad Firmansyah Kasim

The spectral transformation Lanczos method for the sparse symmetric definite generalized eigenvalue problem for matrices $A$ and $B$ is an iterative method that addresses the case of semidefinite or ill conditioned $B$ using a shifted and…

Numerical Analysis · Mathematics 2024-11-07 Michael Stewart

In this article we study the stability problem for positive quaternion-K\"ahler manifolds. We give a description of infinitesimal Einstein deformations and destabilising directions in terms of Laplace eigenfunctions and a special class of…

Differential Geometry · Mathematics 2026-04-03 Yasushi Homma , Uwe Semmelmann

This paper studies the problem of stability of a parameterized delay differential equations (DDE see equation (0.1)). After discretizing the DDE (0.1), we show that the problem can be equivalently casted into a semi-definite programming…

Optimization and Control · Mathematics 2017-01-03 Dongcai Su

We study the construction and convergence of decoupling multistep schemes of higher order using the backward differentiation formulae for an elliptic-parabolic problem, which includes multiple-network poroelasticity as a special case. These…

Numerical Analysis · Mathematics 2025-07-14 Robert Altmann , Abdullah Mujahid , Benjamin Unger
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