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Computational Methods in Applied Mathematics
Article . 2017 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2017
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
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Numerical Approximation of Space-Time Fractional Parabolic Equations

Authors: Joseph E. Pasciak; Andrea Bonito; Wenyu Lei;

Numerical Approximation of Space-Time Fractional Parabolic Equations

Abstract

Abstract In this paper, we develop a numerical scheme for the space-time fractional parabolic equation, i.e. an equation involving a fractional time derivative and a fractional spatial operator. Both the initial value problem and the non-homogeneous forcing problem (with zero initial data) are considered. The solution operator E ⁢ ( t ) {E(t)} for the initial value problem can be written as a Dunford–Taylor integral involving the Mittag-Leffler function e α , 1 {e_{\alpha,1}} and the resolvent of the underlying (non-fractional) spatial operator over an appropriate integration path in the complex plane. Here α denotes the order of the fractional time derivative. The solution for the non-homogeneous problem can be written as a convolution involving an operator W ⁢ ( t ) {W(t)} and the forcing function F ⁢ ( t ) {F(t)} . We develop and analyze semi-discrete methods based on finite element approximation to the underlying (non-fractional) spatial operator in terms of analogous Dunford–Taylor integrals applied to the discrete operator. The space error is of optimal order up to a logarithm of 1 h {\frac{1}{h}} . The fully discrete method for the initial value problem is developed from the semi-discrete approximation by applying a sinc quadrature technique to approximate the Dunford–Taylor integral of the discrete operator and is free of any time stepping. The sinc quadrature of step size k involves k - 2 {k^{-2}} nodes and results in an additional O ⁢ ( exp ⁡ ( - c k ) ) {O(\exp(-\frac{c}{k}))} error. To approximate the convolution appearing in the semi-discrete approximation to the non-homogeneous problem, we apply a pseudo-midpoint quadrature. This involves the average of W h ⁢ ( s ) {W_{h}(s)} , (the semi-discrete approximation to W ⁢ ( s ) {W(s)} ) over the quadrature interval. This average can also be written as a Dunford–Taylor integral. We first analyze the error between this quadrature and the semi-discrete approximation. To develop a fully discrete method, we then introduce sinc quadrature approximations to the Dunford–Taylor integrals for computing the averages. We show that for a refined grid in time with a mesh of O ⁢ ( 𝒩 ⁢ log ⁡ ( 𝒩 ) ) {O({\mathcal{N}}\log({\mathcal{N}}))} intervals, the error between the semi-discrete and fully discrete approximation is O ⁢ ( 𝒩 - 2 + log ⁡ ( 𝒩 ) ⁢ exp ⁡ ( - c k ) ) {O({\mathcal{N}}^{-2}+\log({\mathcal{N}})\exp(-\frac{c}{k}))} . We also report the results of numerical experiments that are in agreement with the theoretical error estimates.

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Keywords

FOS: Mathematics, Mathematics - Numerical Analysis, Numerical Analysis (math.NA)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Top 10%
Average
Top 10%
Green
bronze