{"title":"Inverse source problem for the time-space fractional diffusion equation involving the fractional Sturm–Liouville operator","authors":"Kaiyu Lyu, Hao Cheng","doi":"10.1016/j.cnsns.2025.108772","DOIUrl":null,"url":null,"abstract":"<div><div>In this work, we consider an inverse source problem for the time-space fractional diffusion equation with homogeneous Dirichlet boundary conditions, in which the spatial operator under consideration is the fractional Sturm–Liouville operator. We demonstrate that this inverse source problem is ill-posed in the sense of Hadamard and exhibit the uniqueness and conditional stability of its solution. To recover a stable solution, we employ an iterative generalized quasi-boundary value regularization method. We derive error estimates between the exact and regularized solutions based on both a-priori and a-posteriori choice rules for the regularization parameters. Notably, our method reduces to the generalized quasi-boundary value regularization method after one iteration and exhibits a better error convergence rate. Finally, we present three numerical examples to validate the effectiveness of the used regularization method.</div></div>","PeriodicalId":50658,"journal":{"name":"Communications in Nonlinear Science and Numerical Simulation","volume":"146 ","pages":"Article 108772"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Nonlinear Science and Numerical Simulation","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1007570425001832","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, we consider an inverse source problem for the time-space fractional diffusion equation with homogeneous Dirichlet boundary conditions, in which the spatial operator under consideration is the fractional Sturm–Liouville operator. We demonstrate that this inverse source problem is ill-posed in the sense of Hadamard and exhibit the uniqueness and conditional stability of its solution. To recover a stable solution, we employ an iterative generalized quasi-boundary value regularization method. We derive error estimates between the exact and regularized solutions based on both a-priori and a-posteriori choice rules for the regularization parameters. Notably, our method reduces to the generalized quasi-boundary value regularization method after one iteration and exhibits a better error convergence rate. Finally, we present three numerical examples to validate the effectiveness of the used regularization method.
期刊介绍:
The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity.
The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged.
Topics of interest:
Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity.
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