A scaling-and-squaring method for computing the inverses of matrix $\varphi$-functions

This paper aims to develop efficient numerical methods for computing the inverse of matrix $\varphi$-functions, $\psi_\ell(A):=(\varphi_\ell(A))^(-1)$, for $\ell = 1,2, \dots$ when A is a large and sparse matrix with eigenvalues in the open left half-plane. While $\varphi$-functions play a crucial role in the analysis and implementation of exponential integrators, their inverses arise in solving certain direct and inverse differential problems with non-local boundary conditions. We propose an adaptation of the standard scaling-and-squaring technique for computing $\psi_\ell(A)$, based on the Newton-Schulz iteration for matrix inversion. The convergence of this method is analyzed both theoretically and numerically. In addition, we derive and analyze Padé approximants for approximating $\psi_1(A/2^s)$, where s is a suitably chosen integer, necessary at the root of the squaring process. Numerical experiments demonstrate the effectiveness of the proposed approach.