An Exponential Spectral Method Using VP Means for Semilinear Subdiffusion Equations with Rough Data

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

3 Scopus Citations
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Author(s)

  • Buyang Li
  • Yanping Lin
  • Shu Ma
  • Qiqi Rao

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)2305-2326
Journal / PublicationSIAM Journal on Numerical Analysis
Volume61
Issue number5
Online published9 Oct 2023
Publication statusPublished - 2023

Link(s)

Abstract

A new spectral method is constructed for the linear and semilinear subdiffusion equations with possibly discontinuous rough initial data. The new method effectively combines several computational techniques, including the contour integral representation of the solutions, the quadrature approximation of contour integrals, the exponential integrator using the de la Vallée Poussin means of the source function, and a decomposition of the time interval geometrically refined towards the singularity of the solution and the source function. Rigorous error analysis shows that the proposed method has spectral convergence for the linear and semilinear subdiffusion equations with bounded measurable initial data and possibly singular source functions under the natural regularity of the solutions. © 2023 Society for Industrial and Applied Mathematics Publications. All rights reserved.

Research Area(s)

  • contour integral, convolution quadrature, exponential integrator, geometric decomposition, quadrature approximation, semilinear subdiffusion equation, singularity, spectral method, VP means

Citation Format(s)

An Exponential Spectral Method Using VP Means for Semilinear Subdiffusion Equations with Rough Data. / Li, Buyang; Lin, Yanping; Ma, Shu et al.
In: SIAM Journal on Numerical Analysis, Vol. 61, No. 5, 2023, p. 2305-2326.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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