Jin, B;
Kian, Y;
Zhou, Z;
(2023)
Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time.
SIAM Journal on Applied Mathematics
, 83
(4)
pp. 1496-1517.
10.1137/22M1529105.
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Abstract
Inverse problems of recovering space-dependent parameters, e.g., initial condition, space-dependent source, or potential coefficient in a subdiffusion model from the terminal observation have been extensively studied in recent years. However, all existing studies have assumed that the terminal time at which one takes the observation is exactly known. In this work, we present uniqueness and stability results for three canonical inverse problems, e.g., backward problem, inverse source, and inverse potential problems from the terminal observation at an unknown time. The subdiffusive nature of the problem indicates that one can simultaneously determine the terminal time and space-dependent parameter. The analysis is based on explicit solution representations, asymptotic behavior of the Mittag-Leffler function, and mild regularity conditions on the problem data. Further, we present several one- and two-dimensional numerical experiments to illustrate the feasibility of the approach.
Type: | Article |
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Title: | Inverse Problems for Subdiffusion from Observation at an Unknown Terminal Time |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1137/22M1529105 |
Publisher version: | https://doi.org/10.1137/22M1529105 |
Language: | English |
Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | backward subdiffusion, inverse source problem, inverse potential problem, subdiffusion, unknown terminal time, uniqueness, stability |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10175946 |
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