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research article

A reduced basis approach to large-scale pseudospectra computation

Sirkovic, Petar  
March 1, 2019
Numerical Linear Algebra With Applications

For studying spectral properties of a nonnormal matrix A is an element of Cnxn, information about its spectrum sigma(A) alone is usually not enough. Effects of perturbations on sigma(A) can be studied by computing epsilon-pseudospectra, i.e. the level sets of the resolvent norm function g(z)=||(zI-A)-1||2. The computation of epsilon-pseudospectra requires determining the smallest singular values sigma min(zI-A) for all z on a portion of the complex plane. In this work, we propose a reduced basis approach to pseudospectra computation, which provides highly accurate estimates of pseudospectra in the region of interest, in particular, for pseudospectra estimates in isolated parts of the spectrum containing few eigenvalues of A. It incorporates the sampled singular vectors of zI - A for different values of z, and implicitly exploits their smoothness properties. It provides rigorous upper and lower bounds for the pseudospectra in the region of interest. In addition, we propose a domain splitting technique for tackling numerically more challenging examples. We present a comparison of our algorithms to several existing approaches on a number of numerical examples, showing that our approach provides significant improvement in terms of computational time.

  • Details
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Type
research article
DOI
10.1002/nla.2222
Web of Science ID

WOS:000457614700001

Author(s)
Sirkovic, Petar  
Date Issued

2019-03-01

Publisher

WILEY

Published in
Numerical Linear Algebra With Applications
Volume

26

Issue

2

Article Number

e2222

Subjects

Mathematics, Applied

•

Mathematics

•

large-scale

•

parameter-dependent eigenvalues

•

pseudospectra computation

•

reduced basis

•

subspace acceleration

•

stability

•

approximation

•

eigenvalues

•

algorithms

•

abscissa

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
ANCHP  
Available on Infoscience
February 16, 2019
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/154485
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