Superlinear convergence of the rational Arnoldi method for the approximation of matrix functions

Abstract

A superlinear convergence bound for rational Arnoldi approximations to functions of matrices is derived. This bound generalizes the well-known superlinear convergence bound for the conjugate gradient method to more general functions with finite singularities and to rational Krylov spaces. A constrained equilibrium problem from potential theory is used to characterize a max-min quotient of a nodal rational function underlying the rational Arnoldi approximation, where an additional external field is required for taking into account the poles of the rational Krylov space. The resulting convergence bound is illustrated at several numerical examples, in particular, the convergence of the extended Krylov method for the matrix square root.