GMRES convergence bounds for eigenvalue problems

Freitag, Melina A. and Kürschner, Patrick and Pestana, Jennifer (2018) GMRES convergence bounds for eigenvalue problems. Computational Methods in Applied Mathematics, 18 (2). pp. 203-222. ISSN 1609-9389 (https://doi.org/10.1515/cmam-2017-0017)

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Abstract

The convergence of GMRES for solving linear systems can be influenced heavily by the structure of the right hand side. Within the solution of eigenvalue problems via inverse iteration or subspace iteration, the right hand side is generally related to an approximate invariant subspace of the linear system. We give detailed and new bounds on (block) GMRES that take the special behavior of the right hand side into account and explain the initial sharp decrease of the GMRES residual. The bounds motivate the use of specific preconditioners for these eigenvalue problems, e.g. tuned and polynomial preconditioners, as we describe. The numerical results show that the new (block) GMRES bounds are much sharper than conventional bounds and that preconditioned subspace iteration with either a tuned or polynomial preconditioner should be used in practice.

ORCID iDs

Freitag, Melina A., Kürschner, Patrick and Pestana, Jennifer ORCID logoORCID: https://orcid.org/0000-0003-1527-3178;
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