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A thick-restarted block Arnoldi algorithm with modified Ritz vectors for large eigenproblems

โœ Scribed by Wei Jiang; Gang Wu


Publisher
Elsevier Science
Year
2010
Tongue
English
Weight
807 KB
Volume
60
Category
Article
ISSN
0898-1221

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โœฆ Synopsis


The block Arnoldi method is one of the most commonly used techniques for large eigenproblems. In this paper, we exploit certain modified Ritz vectors to take the place of Ritz vectors in the thick-restarted block Arnoldi algorithm, and propose a modified thickrestarted block Arnoldi algorithm for large eigenproblems. We then consider how to periodically combine the refined subspace iterative method with the modified thick-restarting block Arnoldi algorithm for computing a few dominant eigenpairs of a large matrix. The resulting algorithm is called a Subspace-Block Arnoldi algorithm. Numerical experiments show the efficiency of our new algorithms.


๐Ÿ“œ SIMILAR VOLUMES


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โœ Zhongxiao Jia ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 775 KB

When the matrix in question is uns)xnmetric, the approximate eigenvectors or Ritz vectors obtained by orthogonal projection methods including Arnoldi's method and the block Arnoldi method cannot be guaranteed to converge in theory even if the corresponding approximate eigenvalues or Ritz values do.