Polynomial preconditioning for the action of the matrix square root and inverse square root. ETNA - Electronic Transactions on Numerical Analysis
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1 juillet 2024
- handle: 10670/1.xce6vg
- issn: 1068-9613
- doi: 10.1553/etna_vol60s381
info:eu-repo/semantics/openAccess
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Andreas Frommer et al., « Polynomial preconditioning for the action of the matrix square root and inverse square root. ETNA - Electronic Transactions on Numerical Analysis », Elektronisches Publikationsportal der Österreichischen Akademie der Wissenschafte, ID : 10.1553/etna_vol60s381
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While preconditioning is a long-standing concept to accelerate iterative methods for linear systems, generalizations to matrix functions are still in their infancy. We go a further step in this direction, introducing polynomial preconditioning for Krylov subspace methods that approximate the action of the matrix square root and inverse square root on a vector. Preconditioning reduces the subspace size and therefore avoids the storage problem together with—for non-Hermitian matrices—the increased computational cost per iteration that arises in the unpreconditioned case. Polynomial preconditioning is an attractive alternative to current restarting or sketching approaches since it is simpler and computationally more efficient. We demonstrate this for several numerical examples.