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David Persson

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Preprint Aug 2026

Optimal near-optimality bounds for the Lanczos method for matrix functions

Let $A$ be Hermitian positive definite and let $f_m$ denote the Lanczos approximation to $f(A)b$. We prove that if $f(z)$ or $f(z) / z$ is Stieltjes, then the $A^\alpha$-norm error of the Lanczos approximation is within a factor $\tfrac{1}{2}(\kappa(A)^{E/2} + \kappa(A)^{-E/2})$ of the the best possible Krylov Subspace Method, where $\kappa(A)$ is the condition number of $A$ and $E = \max\{\alpha,1-\alpha\}$. Our result strengthens and generalizes the upper bound of [Schweitzer; SIMAX, 46.3 (2025)]. Moreover, we prove that the constant $\tfrac{1}{2}(\kappa(A)^{E/2} + \kappa(A)^{-E/2})$ is optimal.

Tyler Chen, David Persson · 0 citations