Error bounds for the approximation of matrix functions with rational Krylov methods

Abstract

AbstractWe obtain an expression for the error in the approximation of and with rational Krylov methods, where is a symmetric matrix, is a vector and the function admits an integral representation. The error expression is obtained by linking the matrix function error with the error in the approximate solution of shifted linear systems using the same rational Krylov subspace, and it can be exploited to derive both a priori and a posteriori error bounds. The error bounds are a generalization of the ones given in Chen et al. for the Lanczos method for matrix functions. A technique that we employ in the rational Krylov context can also be applied to refine the bounds for the Lanczos case.