Unique continuation property and Poincaré inequality for higher order fractional Laplacians with applications in inverse problems
Abstract
We prove a unique continuation property for the fractional Laplacian (−Δ)s when s∈(−n/2,∞)∖Z where n≥1. In addition, we study Poincaré-type inequalities for the operator (−Δ)s when s≥0. We apply the results to show that one can uniquely recover, up to a gauge, electric and magnetic potentials from the Dirichlet-to-Neumann map associated to the higher order fractional magnetic Schrödinger equation. We also study the higher order fractional Schrödinger equation with singular electric potential. In both cases, we obtain a Runge approximation property for the equation. Furthermore, we prove a uniqueness result for a partial data problem of the d-plane Radon transform in low regularity. Our work extends some recent results in inverse problems for more general operators.
Main Authors
Format
Articles
Research article
Published
2021
Series
Subjects
Publication in research information system
Publisher
American Institute of Mathematical Sciences (AIMS)
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202110285434Käytä tätä linkitykseen.
Review status
Peer reviewed
ISSN
1930-8337
DOI
https://doi.org/10.3934/ipi.2021009
Language
English
Published in
Inverse Problems and Imaging
Citation
- Covi, G., Mönkkönen, K., & Railo, J. (2021). Unique continuation property and Poincaré inequality for higher order fractional Laplacians with applications in inverse problems. Inverse Problems and Imaging, 15(4), 641-681. https://doi.org/10.3934/ipi.2021009
Funder(s)
Research Council of Finland
Research Council of Finland
European Commission
Funding program(s)
Centre of Excellence, AoF
Academy Project, AoF
ERC Consolidator Grant
Huippuyksikkörahoitus, SA
Akatemiahanke, SA
ERC Consolidator Grant
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Additional information about funding
G.C. was partially supported by the European Research Council under Horizon 2020 (ERC CoG 770924). K.M. and J.R. were partially supported by Academy of Finland (Centre of Excellence in Inverse Modelling and Imaging, grant numbers 284715 and 309963).
Copyright© American Institute of Mathematical Sciences (AIMS), 2021