A Continuous Approach to Computing the Pseudospectra of Linear Operators

Abstract. We propose a continuous approach to computing the pseudospectra of linear operators with compact or compact-plus-scalar resolvent, following a “solve-then-discretize” strategy. Instead of taking a finite section approach or using a finite-dimensional matrix to approximate the operator of interest, the new method employs an operator analogue of the Lanczos process to work with operators and functions directly. The method is shown to be free of spectral pollution and spectral invisibility, fully adaptive, and nearly optimal in accuracy. The advantages of the method are demonstrated by extensive numerical examples and comparison with the traditional method. Reproducibility of computational results. This paper has been awarded the “SIAM Reproducibility Badge: Code and Data Available” as a recognition that the authors have followed reproducibility principles valued by SISC and the scientific computing community. Code and data that allow readers to reproduce the results in this paper are available at https://github.com/kuandeng/PseSp and in the supplementary materials ( PseSp-master.zip [2.29MB]), linked from the main article webpage. [Formula: see text]

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Publication Details

Journal
SIAM Journal on Scientific Computing
Published
2026-11-03
DOI
https://doi.org/10.1137/24m1720135
Primary Topic
Matrix Theory and Algorithms
Type
article
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article

A Continuous Approach to Computing the Pseudospectra of Linear Operators

Kuan Xu, Kuan Deng, Xiaolin Liu
SIAM Journal on Scientific Computing
Matrix Theory and Algorithms
article

A Continuous Approach to Computing the Pseudospectra of Linear Operators

Kuan Xu, Kuan Deng, Xiaolin Liu
article en

Abstract

Abstract. We propose a continuous approach to computing the pseudospectra of linear operators with compact or compact-plus-scalar resolvent, following a “solve-then-discretize” strategy. Instead of taking a finite section approach or using a finite-dimensional matrix to approximate the operator of interest, the new method employs an operator analogue of the Lanczos process to work with operators and functions directly. The method is shown to be free of spectral pollution and spectral invisibility, fully adaptive, and nearly optimal in accuracy. The advantages of the method are demonstrated by extensive numerical examples and comparison with the traditional method. Reproducibility of computational results. This paper has been awarded the “SIAM Reproducibility Badge: Code and Data Available” as a recognition that the authors have followed reproducibility principles valued by SISC and the scientific computing community. Code and data that allow readers to reproduce the results in this paper are available at https://github.com/kuandeng/PseSp and in the supplementary materials ( PseSp-master.zip [2.29MB]), linked from the main article webpage. [Formula: see text]

SIAM Journal on Scientific ComputingVol. 48(6)
University of Science and Technology of China (CN), Hainan University (CN)
Openalex Percentile: Top 99%
Matrix Theory and Algorithms
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