58 citations · 87 across the 4 of their papers we have counts for
4 papers
Computing low-rank approximations of the Fréchet derivative of a matrix function using Krylov subspace methods
Peter Kandolf, Antti Koskela, Samuel D. Relton +1
The Fréchet derivative of the matrix function plays an important role in many different applications, including condition number estimation and network analysis.…
Magnus integrators on multicore CPUs and GPUs
N. Auer, L. Einkemmer, P. Kandolf +1
In the present paper we consider numerical methods to solve the discrete Schrödinger equation with a time dependent Hamiltonian (motivated by problems encountered in the study of s…
Computing the Action of Trigonometric and Hyperbolic Matrix Functions
Nicholas J. Higham, Peter Kandolf
We derive a new algorithm for computing the action of the cosine, sine, hyperbolic cosine, and hyperbolic sine of a matrix on a matrix , without first computing $f(A…
The Leja method revisited: backward error analysis for the matrix exponential
Marco Caliari, Peter Kandolf, Alexander Ostermann +1
The Leja method is a polynomial interpolation procedure that can be used to compute matrix functions. In particular, computing the action of the matrix exponential on a given vecto…