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Robust expansion of subspaces in iterative projection methods for large eigenvalue problems
Author(s) -
Voss Heinrich
Publication year - 2007
Publication title -
pamm
Language(s) - English
Resource type - Journals
ISSN - 1617-7061
DOI - 10.1002/pamm.200700542
Subject(s) - eigenvalues and eigenvectors , linear subspace , quadratic growth , convergence (economics) , projection (relational algebra) , mathematics , jacobi method , mathematical optimization , mathematical analysis , algorithm , pure mathematics , physics , quantum mechanics , economics , economic growth
The Jacobi–Davidson method is known to converge at least quadratically if the correction equation is solved exactly, and it is common experience that the fast convergence is maintained if the correction equation is solved only approximately. Here we derive the Jacobi–Davidson method in a way that explains this robust behavior. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)