Deflation Techniques for an Implicitly Restarted Arnoldi Iteration

dc.contributor.authorLehoucq, R.B.
dc.contributor.authorSorensen, Danny C.
dc.date.accessioned2018-06-18T17:41:50Z
dc.date.available2018-06-18T17:41:50Z
dc.date.issued1994-09
dc.date.noteSeptember 1994 (Revised February 1995)
dc.description.abstractA deflation procedure is introduced that is designed to improve convergence of an implicitly restarted Arnoldi iteration for computing a few eigenvalues of a large matrix. As the iteration progresses the Ritz value approximations of the eigenvalues of A converge at different rates. A numerically stable deflation scheme is introduced that implicitly deflates the converged approximations from the iteration. We present two forms of implicit deflation. The first, a locking operation, decouples converged Ritz values and associated vectors from the active part of the iteration. The second, a purgingoperation, removes unwanted but converged Ritz pairs. Convergence of the iteration is improved and a reduction in computational effort is also achieved. The deflation strategies make it possible to compute multiple or clustered eigenvalues with a single vector restart method. A Block method is not required. These schemes are analyzed with respect to numerical stability and computational results are presented.
dc.format.extent38 pp
dc.identifier.citationLehoucq, R.B. and Sorensen, Danny C.. "Deflation Techniques for an Implicitly Restarted Arnoldi Iteration." (1994) <a href="https://hdl.handle.net/1911/101832">https://hdl.handle.net/1911/101832</a>.
dc.identifier.digitalTR94-13
dc.identifier.urihttps://hdl.handle.net/1911/101832
dc.language.isoeng
dc.titleDeflation Techniques for an Implicitly Restarted Arnoldi Iteration
dc.typeTechnical report
dc.type.dcmiText
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