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Convergence of restarted Krylov subspaces to invariant subspaces

Abstract:

The performance of Krylov subspace eigenvalue algorithms for large matrices can be measured by the angle between a desired invariant subspace and the Krylov subspace. We develop general bounds for this convergence that include the effects of polynomial restarting and impose no restrictions concerning the diagonalizability of the matrix or its degree of non-normality. Associated with a desired set of eigenvalues is a maximum ``reachable invariant subspace'' that can be developed from the given...

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Publication date:
2001-11-05
URN:
uuid:5e31b399-ec20-4bb8-ace9-3f64ba5870f7
Local pid:
oai:eprints.maths.ox.ac.uk:1230

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