Alleviating missing boundary conditions in elliptic partial differential equations using interior point measurements

TL;DR

This paper develops a finite element method for recovering solutions to the Poisson problem with unknown boundary data, using interior point measurements to improve accuracy and reduce regularity requirements.

Contribution

It introduces a novel approach focusing on interior point measurements, providing pointwise error estimates for Riesz representers to enhance recovery accuracy.

Findings

Derived pointwise error estimates for Riesz representers

Achieved improved recovery performance in various norms

Reduced regularity requirements for the solution

Abstract

We consider an optimal recovery problem for the Poisson problem when the boundary data is unknown. Compensating information is provided in the form of a finite number of measurements of the solution. A finite element algorithm for this problem was given in Binev et al. (2024), where measurements were assumed to be either bounded linear functionals of the solution or point measurements at locations lying anywhere in the closure of the computational domain. In contrast, we focus on the case of point measurements at locations lying in the interior of the domain. This lowers the regularity requirements placed on the solution. Also, a key ingredient in the recovery process is the finite element approximation of Riesz representers associated with the measurements. Our main result is a pointwise error estimate for the Riesz representers. We apply this to obtain improved estimates which measure the performance of the recovery algorithm in various norms.