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Adaptive computation of smallest eigenvalues of self‐adjoint elliptic partial differential equations
Author(s) -
Mehrmann Volker,
Miedlar Agnieszka
Publication year - 2011
Publication title -
numerical linear algebra with applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.02
H-Index - 53
eISSN - 1099-1506
pISSN - 1070-5325
DOI - 10.1002/nla.733
Subject(s) - eigenvalues and eigenvectors , mathematics , solver , discretization , finite element method , divide and conquer eigenvalue algorithm , partial differential equation , krylov subspace , computation , polygon mesh , elliptic partial differential equation , subspace topology , iterative method , mathematical optimization , algorithm , mathematical analysis , geometry , physics , quantum mechanics , thermodynamics
We consider a new adaptive finite element (AFEM) algorithm for self‐adjoint elliptic PDE eigenvalue problems. In contrast to other approaches we incorporate the inexact solutions of the resulting finite‐dimensional algebraic eigenvalue problems into the adaptation process. In this way we can balance the costs of the adaptive refinement of the mesh with the costs for the iterative eigenvalue method. We present error estimates that incorporate the discretization errors, approximation errors in the eigenvalue solver and roundoff errors, and use these for the adaptation process. We show that it is also possible to restrict to very few iterations of a Krylov subspace solver for the eigenvalue problem on coarse meshes. Several examples are presented to show that this new approach achieves much better complexity than the previous AFEM approaches which assume that the algebraic eigenvalue problem is solved to full accuracy. Copyright © 2010 John Wiley & Sons, Ltd.