A Comparison of Limited-memory Krylov Methods for Stieltjes Functions of Hermitian Matrices
Stefan Güttel, Marcel Schweitzer · SIAM Journal on Matrix Analysis and Applications · 2021
Given a limited amount of memory and a target accuracy, we propose and compare several polynomial Krylov methods for the approximation of $f(A){b}$, the action of a Stieltjes matrix function of a large Hermitian matrix on a vector. Using new error bounds and estimates, as well as existing results, we derive predictions of the practical performance of the methods and rank them accordingly. As byproducts, we derive new results on inexact Krylov iterations for matrix functions in order to allow for a fair comparison of rational Krylov methods with polynomial inner solves.