Jacobi-Davidson methods for cubic eigenvalue problems

Several Jacobi–Davidson type methods are proposed for computing interior eigenpairs of large‐scale cubic eigenvalue problems. To successively compute the eigenpairs, a novel explicit non‐equivalence deflation method with low‐rank updates is developed and analysed. Various techniques such as locking,...

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Bibliographic Details
Published inNumerical linear algebra with applications Vol. 12; no. 7; pp. 605 - 624
Main Authors Hwang, Tsung-Min, Lin, Wen-Wei, Liu, Jinn-Liang, Wang, Weichung
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.09.2005
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Summary:Several Jacobi–Davidson type methods are proposed for computing interior eigenpairs of large‐scale cubic eigenvalue problems. To successively compute the eigenpairs, a novel explicit non‐equivalence deflation method with low‐rank updates is developed and analysed. Various techniques such as locking, search direction transformation, restarting, and preconditioning are incorporated into the methods to improve stability and efficiency. A semiconductor quantum dot model is given as an example to illustrate the cubic nature of the eigenvalue system resulting from the finite difference approximation. Numerical results of this model are given to demonstrate the convergence and effectiveness of the methods. Comparison results are also provided to indicate advantages and disadvantages among the various methods. Copyright © 2004 John Wiley & Sons, Ltd.
Bibliography:National Center for Theoretical Sciences
National Science Council
ark:/67375/WNG-35FP5J8P-3
ArticleID:NLA423
istex:C76393D04EE73C0FBEB206687D3035DCA7D35A11
ISSN:1070-5325
1099-1506
DOI:10.1002/nla.423