Perturbed Arnoldi Method for Computing Multiple Eigenvalues

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dc.contributor.advisorMorgan, Ronald Benjamin, 1958-
dc.contributor.authorGibson, Thomas
dc.contributor.departmentMathematics.en_US
dc.contributor.otherBaylor University.en_US
dc.date.accessioned2014-06-02T18:35:40Z
dc.date.available2014-06-02T18:35:40Z
dc.date.copyright2014
dc.date.issued2014-06-02
dc.description.abstractThere are several known methods for computing eigenvalues of a large sparse nonsymmetric matrix. One of the most efficient methods is known as the Arnoldi method. The Arnoldi method is a Krylov subspace method that computes the eigenvalues of the projection of a matrix onto the Krylov subspace. In our investigation, we present both non-restarted and restarted Arnoldi methods and examine how round-off error helps find multiple eigenvalues. We introduce a new method that uses a diagonal matrix perturbation that separates multiple eigenvalues and improves performance. Our approach presents an alternative that avoids the need for a block method, or for relying on round-off error to introduce multiple copies of eigenvalues.en_US
dc.identifier.urihttp://hdl.handle.net/2104/8991
dc.language.isoen_USen_US
dc.rightsBaylor University projects are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact libraryquestions@baylor.edu for inquiries about permission.en_US
dc.rights.accessrightsWorldwide accessen_US
dc.subjectNumerical linear algebra.en_US
dc.subjectKrylov subspace methods.en_US
dc.subjectArnoldi method.en_US
dc.subjectEigenvalue algorithms.en_US
dc.titlePerturbed Arnoldi Method for Computing Multiple Eigenvaluesen_US
dc.typeThesisen_US

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