Alleviating missing boundary conditions in elliptic partial differential equations using interior point measurements
This work addresses a specific challenge in computational mathematics for PDE solvers, but it is incremental as it builds on prior methods by focusing on interior measurements to lower regularity requirements.
The paper tackles the problem of recovering solutions to elliptic PDEs with unknown boundary conditions using only interior point measurements, and presents improved error estimates for the recovery algorithm in various norms.
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.