In many physical situations, a few specific eigenvalues of a large sparse generalized eigenvalue problem Ax = lambda Bx are needed. If exact linear solves with A-sigma B are available, implicitly restarted Arnoldi with purification is a common approach for problems where B is positive semidefinite. In this paper, a new approach based on implicitly restarted Arnoldi will be presented that avoids most of the problems due to the singularity of B. Secondly, if exact solves are not available, Jacobi-Davidson QZ will be presented as a robust method to compute a few specific eigenvalues. Results are illustrated by numerical experiments.
CITATION STYLE
Rommes, J. (2007). Arnoldi and Jacobi-Davidson methods for generalized eigenvalue problems $Ax=\lambda Bx$ with singular $B$. Mathematics of Computation, 77(262), 995–1016. https://doi.org/10.1090/s0025-5718-07-02040-6
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