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Journal of Scientific Computing

Erschienen in:

06.09.2018

Convergence Analysis of Krylov Subspace Spectral Methods for Reaction–Diffusion Equations

verfasst von: Somayyeh Sheikholeslami, James V. Lambers, Carley Walker

Erschienen in: Journal of Scientific Computing | Ausgabe 3/2019

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Abstract

Krylov subspace spectral (KSS) methods are explicit time-stepping methods for partial differential equations that are designed to extend the advantages of Fourier spectral methods, when applied to constant-coefficient problems, to the variable-coefficient case. This paper presents a convergence analysis of a first-order KSS method applied to a system of coupled equations for modeling first-order photobleaching kinetics. The analysis confirms what has been observed in numerical experiments—that the method is unconditionally stable and achieves spectral accuracy in space. Further analysis shows that this unconditional stability is not limited to the case in which the leading coefficient is constant.

Vorheriger Artikel Computing Integrals Involved the Gaussian Function with a Small Standard Deviation

Nächster Artikel An Adaptive Infeasible-Interior-Point Method with the One-Norm Wide Neighborhood for Semi-definite Programming

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Titel: Convergence Analysis of Krylov Subspace Spectral Methods for Reaction–Diffusion Equations
verfasst von: Somayyeh Sheikholeslami
James V. Lambers
Carley Walker
Publikationsdatum: 06.09.2018
Verlag: Springer US
Erschienen in: Journal of Scientific Computing / Ausgabe 3/2019
Print ISSN: 0885-7474
Elektronische ISSN: 1573-7691
DOI: https://doi.org/10.1007/s10915-018-0824-5

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