A Computational Method for the Inverse Robin Problem with Convergence Rate
Erik Burman, Marvin Knöller, Lauri Oksanen
公開日: 2025/9/22
Abstract
The inverse Robin problem covers the determination of the Robin parameter in an elliptic partial differential equation posed on a domain $\Omega$. Given the solution of the Robin problem on a subdomain $\omega \subset \Omega$ together with the elliptic problem's right hand sides, the aim is to solve this inverse Robin problem numerically. In this work, a computational method for the reconstruction of the Robin parameter inspired by a unique continuation method is established. The proposed scheme relies solely on first-order Lagrange finite elements ensuring a straightforward implementation. Under the main assumption that the Robin parameter is in a finite dimensional space of continuously differentiable functions it is shown that the numerical method is second order convergent in the finite element's mesh size. For noisy data this convergence rate is shown to hold true until the noise term dominates the error estimate. Numerical experiments are presented that highlight the feasibility of the Robin parameter reconstruction and that confirm the theoretical convergence results numerically.