AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
PDF (2.9 MB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Convergence of an energy-preserving finite difference method for the nonlinear coupled space-fractional Klein-Gordon equations

Min Li1Ju Ming2Tingting Qin2Boya Zhou3( )
School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China, and Hubei Key Laboratory of Engineering Modeling and Scientific Computing, Huazhong University of Science and Technology, Wuhan 430074, China
School of Mathematics and Big Data, Foshan University, Guangdong, 52800, China
Show Author Information

Abstract

An energy-preserving finite difference method is first presented for solving the nonlinear coupled space-fractional Klein-Gordon (KG) equations. The discrete conservation law, boundedness of the numerical solutions and convergence of the numerical schemes are obtained. These results are proved by the recent developed fractional Sobolev inequalities, the matrix analytical methods and so on. Numerical experiments are carried out to confirm the theoretical findings.

References

【1】
【1】
 
 
Networks and Heterogeneous Media
Pages 957-981

{{item.num}}

Comments on this article

Go to comment

< Back to all reports

Review Status: {{reviewData.commendedNum}} Commended , {{reviewData.revisionRequiredNum}} Revision Required , {{reviewData.notCommendedNum}} Not Commended Under Peer Review

Review Comment

Close
Close
Cite this article:
Li M, Ming J, Qin T, et al. Convergence of an energy-preserving finite difference method for the nonlinear coupled space-fractional Klein-Gordon equations. Networks and Heterogeneous Media, 2023, 18(3): 957-981. https://doi.org/10.3934/nhm.2023042

133

Views

1

Downloads

2

Crossref

2

Web of Science

2

Scopus

Received: 28 December 2022
Revised: 25 February 2023
Accepted: 05 March 2023
Published: 15 September 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)