Stabilizing the Rayleigh--Ritz procedure by randomization

Fuente: arXiv
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Main Author: Shao, Nian
Format: Preprint
Published: 2026
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author Shao, Nian
author_facet Shao, Nian
contents Extracting approximate eigenpairs from a prescribed subspace is of fundamental importance in eigenvalue computation. While projecting the target eigenvector onto the subspace yields satisfactory accuracy, extracting an approximate eigenpair that attains a comparable convergence rate has remained a long-standing open problem. Although the standard Rayleigh--Ritz procedure is widely used for this purpose, it may suffer from deteriorated convergence of Ritz values and may even fail to produce convergent Ritz vectors. In this paper, we address this long-standing open problem by introducing a randomized Rayleigh--Ritz procedure whose output converges at a rate similar to the ideal projection. Our analysis requires only the simplicity of the target eigenvalue and extends naturally to nonlinear eigenvalue problems.
format Preprint
id arxiv_https___arxiv_org_abs_2604_01037
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Stabilizing the Rayleigh--Ritz procedure by randomization
Shao, Nian
Numerical Analysis
Extracting approximate eigenpairs from a prescribed subspace is of fundamental importance in eigenvalue computation. While projecting the target eigenvector onto the subspace yields satisfactory accuracy, extracting an approximate eigenpair that attains a comparable convergence rate has remained a long-standing open problem. Although the standard Rayleigh--Ritz procedure is widely used for this purpose, it may suffer from deteriorated convergence of Ritz values and may even fail to produce convergent Ritz vectors. In this paper, we address this long-standing open problem by introducing a randomized Rayleigh--Ritz procedure whose output converges at a rate similar to the ideal projection. Our analysis requires only the simplicity of the target eigenvalue and extends naturally to nonlinear eigenvalue problems.
title Stabilizing the Rayleigh--Ritz procedure by randomization
topic Numerical Analysis
url https://arxiv.org/abs/2604.01037