UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Convergence rate analysis of Galerkin approximation of inverse potential problem

Jin, Bangti; Lu, Xiliang; Quan, Qimeng; Zhou, Zhi; (2023) Convergence rate analysis of Galerkin approximation of inverse potential problem. Inverse Problems , 39 (1) , Article 015008. 10.1088/1361-6420/aca70e. Green open access

[thumbnail of 2203.04899v2.pdf]
Preview
Text
2203.04899v2.pdf - Accepted Version

Download (818kB) | Preview

Abstract

In this work we analyze the inverse problem of recovering a space-dependent potential coefficient in an elliptic / parabolic problem from distributed observation. We establish novel (weighted) conditional stability estimates under very mild conditions on the problem data. Then we provide an error analysis of a standard reconstruction scheme based on the standard output least-squares formulation with Tikhonov regularization (by an H^{1} -seminorm penalty), which is then discretized by the Galerkin finite element method with continuous piecewise linear finite elements in space (and also backward Euler method in time for parabolic problems). We present a detailed error analysis of the discrete scheme, and provide convergence rates in a weighted L^{2}(omega) for discrete approximations with respect to the exact potential. The error bounds explicitly depend on the noise level, regularization parameter and discretization parameter(s). Under suitable conditions, we also derive error estimates in the standard L^{2}(omega) and interior L^{2} norms. The analysis employs sharp a priori error estimates and nonstandard test functions. Several numerical experiments are given to complement the theoretical analysis.

Type: Article
Title: Convergence rate analysis of Galerkin approximation of inverse potential problem
Open access status: An open access version is available from UCL Discovery
DOI: 10.1088/1361-6420/aca70e
Publisher version: https://doi.org/10.1088/1361-6420%2Faca70e
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions.
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.ucl.ac.uk/id/eprint/10161670
Downloads since deposit
7Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item