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 (284.9 KB)
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article | Open Access

Approximate inverse preconditioners for linear systems arising from spatial balanced fractional diffusion equations

Xiaofeng GuoJianyu Pan( )
School of Mathematical Sciences, East China Normal Universiy, Shanghai 200241, China
Show Author Information

Abstract

We consider the preconditioned iterative methods for the linear systems arising from the finite volume discretization of spatial balanced fractional diffusion equations where the fractional differential operators are comprised of both Riemann-Liouville and Caputo fractional derivatives. The coefficient matrices of the linear systems consist of the sum of tridiagonal matrix and Toeplitz-times-diagonal-times-Toeplitz matrix. We propose using symmetric approximate inverse preconditioners to solve such linear systems. We show that the spectra of the preconditioned matrices are clustered around 1. Numerical examples, for both one and two dimensional problems, are given to demonstrate the efficiency of the new preconditioners.

CLC number: 65F08, 65F10

References

【1】
【1】
 
 
AIMS Mathematics
Pages 17284-17306

{{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:
Guo X, Pan J. Approximate inverse preconditioners for linear systems arising from spatial balanced fractional diffusion equations. AIMS Mathematics, 2023, 8(7): 17284-17306. https://doi.org/10.3934/math.2023884

7

Views

0

Downloads

0

Crossref

0

Web of Science

1

Scopus

Received: 28 April 2023
Revised: 16 May 2023
Accepted: 16 May 2023
Published: 15 July 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)