Error Analysis of the Inverse Conductivity Problem with Scattered Measurements

Abstract: In this work, we investigate the inverse problem of recovering the conductivity coefficient in an elliptic equation from noisy measurements collected at finitely many deterministic scattered points in the domain $Ω$, and corrupted by random noise. Inspired by the regularity analysis, we propose a numerical scheme based on the regularized least-squares formulation with a $W<sup>{1,4}(Ω)$ penalty, and discretize the regularized problem using the Galerkin finite element method with continuous piecewise linear elements. Under suitable assumptions on the problem data, we provide an error analysis of the regularized solution and its Galerkin approximation. We establish $L<sup>2(Ω)$ error bounds in a high-probability sense, which depend explicitly on the regularization parameter $γ$, the number $n$ of data points and the mesh size $h$. We also present numerical experiments to illustrate the theoretical findings.