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