Stability estimates for the inverse fractional conductivity problem
Giovanni Covi, Jesse Railo, Teemu Tyni, Philipp Zimmermann

TL;DR
This paper establishes a logarithmic stability estimate for the inverse fractional conductivity problem on smooth domains, advancing understanding of the problem's stability and optimality in the context of nonlocal equations.
Contribution
It provides the first resolution of technical challenges in deriving stability estimates for the fractional conductivity inverse problem, extending classical results to a nonlocal setting.
Findings
Logarithmic stability estimate for the inverse fractional conductivity problem
Proof of the optimality of the stability estimates
Extension of classical stability results to fractional and nonlocal equations
Abstract
We study the stability of an inverse problem for the fractional conductivity equation on bounded smooth domains. We obtain a logarithmic stability estimate for the inverse problem under suitable a priori bounds on the globally defined conductivities. The argument has three main ingredients: 1. the logarithmic stability of the related inverse problem for the fractional Schr\"odinger equation by R\"uland and Salo; 2. the Lipschitz stability of the exterior determination problem; 3. utilizing and identifying nonlocal analogies of Alessandrini's work on the stability of the classical Calder\'on problem. The main contribution of the article is the resolution of the technical difficulties related to the last mentioned step. Furthermore, we show the optimality of the logarithmic stability estimates, following the earlier works by Mandache on the instability of the inverse conductivity problem,…
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 · Stability and Controllability of Differential Equations
