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ADCM
2011

Perturbed preconditioned inverse iteration for operator eigenvalue problems with applications to adaptive wavelet discretization

13 years 7 months ago
Perturbed preconditioned inverse iteration for operator eigenvalue problems with applications to adaptive wavelet discretization
ABSTRACT. In this paper we discuss an abstract iteration scheme for the calculation of the smallest eigenvalue of an elliptic operator eigenvalue problem. A short and geometric proof based on the preconditioned inverse iteration (PINVIT) for matrices [Knyazev and Neymeyr, (2008)] is extended to the case of operators. We show that convergence is retained up to any tolerance if one only uses approximate applications of operators which leads to the perturbed preconditioned inverse iteration (PPINVIT). We then analyze the Besov regularity of the eigenfunctions of the Poisson eigenvalue problem on a polygonal domain, showing the advantage of an adaptive solver to uniform refinement when using a stable wavelet base. A numerical example for PPINVIT, applied to the model problem on the L-shaped domain, is shown to reproduce the predicted behaviour.
Thorsten Rohwedder, Reinhold Schneider, Andreas Ze
Added 12 May 2011
Updated 12 May 2011
Type Journal
Year 2011
Where ADCM
Authors Thorsten Rohwedder, Reinhold Schneider, Andreas Zeiser
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