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Arnoldi and Jacobi-Davidson methods for generalized eigenvalue problems $ Ax=\lambda Bx$ with singular $ B$


Author: Joost Rommes
Journal: Math. Comp. 77 (2008), 995-1015
MSC (2000): Primary 65F15, 65F50
DOI: https://doi.org/10.1090/S0025-5718-07-02040-6
Published electronically: December 10, 2007
MathSciNet review: 2373189
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Abstract: In many physical situations, a few specific eigenvalues of a large sparse generalized eigenvalue problem $ Ax=\lambda Bx$ are needed. If exact linear solves with $ A-\sigma B$ are available, implicitly restarted Arnoldi with purification is a common approach for problems where $ B$ is positive semidefinite. In this paper, a new approach based on implicitly restarted Arnoldi will be presented that avoids most of the problems due to the singularity of $ B$. Secondly, if exact solves are not available, Jacobi-Davidson QZ will be presented as a robust method to compute a few specific eigenvalues. Results are illustrated by numerical experiments.


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Additional Information

Joost Rommes
Affiliation: Mathematical Institute, Utrecht University, P.O. Box 80010, NL-3508 TA Utrecht, The Netherlands
Address at time of publication: NXP Semiconductors, Corporate I&T / DTF, High Tech Campus 37, PostBox WY4-01, NL-5656 AE, Eindhoven, The Netherlands
Email: joost.rommes@nxp.com

DOI: https://doi.org/10.1090/S0025-5718-07-02040-6
Keywords: Sparse generalized eigenvalue problems, purification, semi-inner product, implicitly restarted Arnoldi, Jacobi-Davidson, preconditioning
Received by editor(s): March 29, 2005
Received by editor(s) in revised form: January 25, 2007
Published electronically: December 10, 2007
Additional Notes: The author was supported by the BRICKS-MSV1 project.
Article copyright: © Copyright 2007 American Mathematical Society
The copyright for this article reverts to public domain 28 years after publication.

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