2014.28: Convergence of restarted Krylov subspace methods for Stieltjes functions of matrices
2014.28: Frommer Andreas, Güttel Stefan and Schweitzer Marcel (2014) Convergence of restarted Krylov subspace methods for Stieltjes functions of matrices.
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To approximate f(A)b---the action of a matrix function on a vector---by a Krylov subspace method, restarts may become mandatory due to storage requirements for the Arnoldi basis or due to the growing computational complexity of evaluating f on a Hessenberg matrix of growing size. A number of restarting methods have been proposed in the literature in recent years and there has been substantial algorithmic advancement concerning their stability and computational efficiency. However, the question under which circumstances convergence of these methods can be guaranteed has remained largely unanswered. In this paper we consider the class of Stieltjes functions and a related class, which contains important functions like the (inverse) square root and the matrix logarithm. For these classes of functions we present new theoretical results which prove convergence for Hermitian positive definite matrices A and arbitrary restart lengths. We also propose a modification of the Arnoldi approximation which guarantees convergence for the same classes of functions and any restart length if A is not necessarily Hermitian but positive real.
|Item Type:||MIMS Preprint|
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|Uncontrolled Keywords:||matrix functions, Krylov subspace methods, restarted Arnoldi method, conjugate gradient method, shifted linear systems, shifted GMRES method, harmonic Ritz values|
|Subjects:||MSC 2000 > 65 Numerical analysis|
|Deposited By:||Stefan Güttel|
|Deposited On:||01 October 2014|
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