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On the convergence of a two-level preconditioned Jacobi-Davidson method for eigenvalue problems


Authors: Wei Wang and Xuejun Xu
Journal: Math. Comp. 88 (2019), 2295-2324
MSC (2010): Primary 65N30, 65N55
DOI: https://doi.org/10.1090/mcom/3403
Published electronically: December 20, 2018
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Abstract: In this paper, we shall give a rigorous theoretical analysis of the two-level preconditioned Jacobi-Davidson method for solving the large scale discrete elliptic eigenvalue problems, which was essentially proposed by Zhao, Hwang, and Cai in 2016. Focusing on eliminating the error components in the orthogonal complement space of the target eigenspace, we find that the method could be extended to the case of the $ 2m$th order elliptic operator ($ m=1,2$). By choosing a suitable coarse space, we prove that the method holds a good scalability and we obtain the error reduction $ \gamma =c(1-C\frac {\delta ^{2m-1}}{H^{2m-1}}) $ in each iteration, where $ C $ is a constant independent of the mesh size $ h $ and the diameter of subdomains $ H $, $ \delta $ is the overlapping size among the subdomains, and $ c\rightarrow 1$ decreasingly as $ H\rightarrow 0 $. Moreover, the method does not need any assumption between $ H $ and $ h $. Numerical results supporting our theory are given.


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Additional Information

Wei Wang
Affiliation: Beijing Computational Science Research Center, Beijing 100193, People’s Republic of China; and LSEC, Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, P.O. Box 2719, Beijing 100190, People’s Republic of China
Email: ww@csrc.ac.cn

Xuejun Xu
Affiliation: School of Mathematical Sciences, Tongji University, Shanghai 200442, People’s Republic of China; and LSEC, Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, P.O. Box 2719, Beijing 100190, People’s Republic of China
Email: xxj@lsec.cc.ac.cn

DOI: https://doi.org/10.1090/mcom/3403
Keywords: Jacobi--Davidson method, eigenvalue problems, domain decomposition method
Received by editor(s): May 8, 2018
Received by editor(s) in revised form: August 25, 2018, and September 5, 2018
Published electronically: December 20, 2018
Additional Notes: The work of the first author was supported by the National Natural Science Foundation of China (Grant No. U1530401).
The work of the second author was supported by the National Natural Science Foundation of China (Grant No. 11671302).
Article copyright: © Copyright 2018 American Mathematical Society