Block triangular preconditioning for inverse source problems in time-space fractional diffusion equations

Fuente: arXiv
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Auteurs principaux: Majumdar, Monoswini, Serra-Capizzano, Stefano, Sormani, Rosita L.
Format: Preprint
Publié: 2025
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author Majumdar, Monoswini
Serra-Capizzano, Stefano
Sormani, Rosita L.
author_facet Majumdar, Monoswini
Serra-Capizzano, Stefano
Sormani, Rosita L.
contents The current work investigates the effectiveness of block triangular preconditioners in accelerating and stabilizing the numerical solution of inverse source problems governed by time-space fractional diffusion equations (TSFDEs). We focus on the recovery of an unknown spatial source function in a multi-dimensional TSFDE, incorporating Caputo time-fractional derivatives and the fractional Laplacian. The inherent ill-posedness is addressed via a quasi-boundary value regularization, followed by a finite difference discretization that leads to large, structured linear systems. We develop and analyze a block triangular preconditioning strategy that mimics the coefficient matrix, while simplifying its structure for computational efficiency. Numerical experiments using the GMRES solver demonstrate that the proposed preconditioner significantly improve convergence rates, robustness, and accuracy, making it well-suited for large-scale, real-world inverse problems involving fractional modeling.
format Preprint
id arxiv_https___arxiv_org_abs_2507_02809
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Block triangular preconditioning for inverse source problems in time-space fractional diffusion equations
Majumdar, Monoswini
Serra-Capizzano, Stefano
Sormani, Rosita L.
Numerical Analysis
65F10 (65F08, 15A18, 15B05, 65R32)
The current work investigates the effectiveness of block triangular preconditioners in accelerating and stabilizing the numerical solution of inverse source problems governed by time-space fractional diffusion equations (TSFDEs). We focus on the recovery of an unknown spatial source function in a multi-dimensional TSFDE, incorporating Caputo time-fractional derivatives and the fractional Laplacian. The inherent ill-posedness is addressed via a quasi-boundary value regularization, followed by a finite difference discretization that leads to large, structured linear systems. We develop and analyze a block triangular preconditioning strategy that mimics the coefficient matrix, while simplifying its structure for computational efficiency. Numerical experiments using the GMRES solver demonstrate that the proposed preconditioner significantly improve convergence rates, robustness, and accuracy, making it well-suited for large-scale, real-world inverse problems involving fractional modeling.
title Block triangular preconditioning for inverse source problems in time-space fractional diffusion equations
topic Numerical Analysis
65F10 (65F08, 15A18, 15B05, 65R32)
url https://arxiv.org/abs/2507.02809