Deflated block Krylov subspace methods for large scale eigenvalue problems

Authors:
Qiang Niu;Linzhang Lu
Affiliations:
College of Mathematical Science, Qingdao University, Qingdao 266071, PR China and BNU-HKBU United International College, Zhuhai, 519085, PR China;School of Mathematics and Computer Science, Guizhou Normal University, Guiyang 550001, PR China and School of Mathematical Sciences, Xiamen University, Xiamen 361005, PR China
Venue:
Journal of Computational and Applied Mathematics
Year:
2010

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Abstract

We discuss a class of deflated block Krylov subspace methods for solving large scale matrix eigenvalue problems. The efficiency of an Arnoldi-type method is examined in computing partial or closely clustered eigenvalues of large matrices. As an improvement, we also propose a refined variant of the Arnoldi-type method. Comparisons show that the refined variant can further improve the Arnoldi-type method and both methods exhibit very regular convergence behavior.