Point measurements for a Neumann-to-Dirichlet map and the Calder\'on problem in the plane
Nuutti Hyv\"onen, Petteri Piiroinen, Otto Seiskari

TL;DR
This paper demonstrates that point measurements of potential differences, called bisweep data, uniquely determine the Neumann-to-Dirichlet map and lead to a new local uniqueness result for the Calderón inverse conductivity problem in the plane.
Contribution
It introduces a novel approach using bisweep data and their derivatives to uniquely identify the Neumann-to-Dirichlet map and the conductivity in a local setting in two dimensions.
Findings
Bisweep data extend as a holomorphic function in 2D.
Derivatives of bisweep data at a point determine the Neumann-to-Dirichlet map.
Point measurements can uniquely identify the conductivity locally.
Abstract
This work considers properties of the Neumann-to-Dirichlet map for the conductivity equation under the assumption that the conductivity is identically one close to the boundary of the examined smooth, bounded and simply connected domain. It is demonstrated that the so-called bisweep data, i.e., the (relative) potential differences between two boundary points when delta currents of opposite signs are applied at the very same points, uniquely determine the whole Neumann-to-Dirichlet map. In two dimensions, the bisweep data extend as a holomorphic function of two variables to some (interior) neighborhood of the product boundary. It follows that the whole Neumann-to-Dirichlet map is characterized by the derivatives of the bisweep data at an arbitrary point. On the diagonal of the product boundary, these derivatives can be given with the help of the derivatives of the (relative) boundary…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNumerical methods in inverse problems · Advanced Mathematical Modeling in Engineering · Probabilistic and Robust Engineering Design
