Jitse Niesen
University of Leeds
38 Papers
316 Citations
Jitse Niesen is an academic researcher from University of Leeds. The author has contributed to research in topics: Boundary value problem & Numerical analysis. The author has an hindex of 12, co-authored 36 publications. Previous affiliations of Jitse Niesen include Heriot-Watt University & University of Cambridge.
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Papers
Algorithm 919: A Krylov Subspace Algorithm for Evaluating the ϕ-Functions Appearing in Exponential Integrators
Jitse Niesen,W. M. Wright +1 more
TL;DR: An algorithm for computing the solution of a large system of linear ordinary differential equations (ODEs) with polynomial inhomogeneity using Arnoldi or Lanczos iteration and projecting the function on this subspace using time-stepping to prevent the Krylov subspace from growing too large.
253
A Krylov subspace algorithm for evaluating the phi-functions appearing in exponential integrators
Jitse Niesen,W. M. Wright +1 more
TL;DR: In this article, an adaptive algorithm for computing the solution of a large system of linear ordinary dierential equations (ODEs) with polynomial in-homogeneity is presented, where the action of the matrix function is computed by constructing a Krylov subspace using Arnoldi or Lanczos iteration and projecting the function on this subspace.
Convergence of the Magnus series
P. C. Moan,Jitse Niesen +1 more
TL;DR: The main result establishes a sufficient condition for convergence, which improves on several earlier results and establishes the basis of the Magnus series.
114
Convergence of the Magnus Series
P. C. Moan,Jitse Niesen +1 more
TL;DR: In this paper, a sufficient condition for convergence of the Magnus series is established. But the main result of this paper is that it is not a necessary condition for the series to converge.
96
Computing stability of multidimensional traveling waves
TL;DR: In this article, the pure point spectrum associated with the linear stability of multidimensional traveling fronts to parabolic nonlinear systems is computed based on the Evans function shooting approach, which generates a large, linear, one-dimensional system of equations for the longitudinal Fourier coefficients.