We present an efficient inexact implicitly restarted Arnoldi algorithm to find a few eigenpairs of large unitary matrices. The approximating Krylov spaces are built using short-term recurrences derived from Gragg's isometric Arnoldi process. The implicit restarts are done by the Krylov-Schur methodo
The effects of inexact solvers in algorithms for symmetric eigenvalue problems
β Scribed by P. Smit; M.H.C. Paardekooper
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 797 KB
- Volume
- 287
- Category
- Article
- ISSN
- 0024-3795
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β¦ Synopsis
This paper analyses the effects of inaccurate linear solvers on the behaviour of inverse iteration and Rayleigh quotient iteration. We derive an expression for the worst-case perturbation of the convergence factor of the exact iteration, due to the inexact solution.
A necessary and sufficient condition on the approximate eigenvector for the improvement of the next iterate follows from that formula. Preceding this, several new inequalities describe the relation between the errors in the approximate eigenvector, the approximate eigenvalue and the corresponding residual.
π SIMILAR VOLUMES
The standard BDDC (balancing domain decomposition by constraints) preconditioner is shown to be equivalent to a preconditioner built from a partially subassembled finite element model. This results in a system of linear algebraic equations which is much easier to solve in parallel than the fully ass
The implicit QR algorithm is a serial iterative algorithm for determining all the eigenvalues of an \(n \times n\) symmetric tridiagonal matrix \(A\). About \(3 n\) iterations, each requiring the serial application of about \(n\) similarity planar transformations, are required to reduce \(A\) to dia