Abstract
In order to solve all or some eigenvalues lied in a cluster, we propose a weighted block Golub-Kahan-Lanczos algorithm for the linear response eigenvalue problem. Error bounds of the approximations to an eigenvalue cluster, as well as their corresponding eigenspace, are established and show the advantages. A practical thick-restart strategy is applied to the block algorithm to eliminate the increasing computational and memory costs, and the numerical instability. Numerical examples illustrate the effectiveness of our new algorithms.
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Natural Science Foundation of Jiangsu Province
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Cited by
2 articles.
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