390
Views
6
CrossRef citations to date
0
Altmetric
Original Articles

A high-order difference scheme for the fractional sub-diffusion equation

, &
Pages 405-426 | Received 17 Apr 2015, Accepted 01 Oct 2015, Published online: 08 Dec 2015
 

ABSTRACT

Based on the Lubich's high-order operators, a second-order temporal finite-difference method is considered for the fractional sub-diffusion equation. It has been proved that the finite-difference scheme is unconditionally stable and convergent in L2 norm by the energy method in both one- and two-dimensional cases. The rate of convergence is order of two in temporal direction under the initial value satisfying some suitable conditions. Some numerical examples are given to confirm the theoretical results.

2010 AMS SUBJECT CLASSIFICATIONS:

Acknowledgments

The authors are grateful to anonymous referees for their valuable comments and suggestions to improve this work.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research is supported by National Natural Science Foundation of China [No. 11271068] and by the Fundamental Research Funds for the Central Universities and the Research and Innovation Project for College Graduates of Jiangsu Province [Grant No.: KYLX_0081]. G. Lin would like to thank the support of the Multifaceted Mathematics for Complex Energy Systems (M2ACS) project, the Collaboratory on Mathematics for Mesoscopic Modelling of Materials project and NSF Grant DMS-1115887.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,129.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.