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Reconstruction and stability in Gelfand’s inverseinterior spectral problem

Roberta Bosi, Yaroslav Kurylev, Matti Lassas

2022Analysis & PDE22 citationsDOI

Abstract

Assume that $M$ is a compact Riemannian manifold of bounded geometry given by restrictions on its diameter, Ricci curvature and injectivity radius. Assume we are given, with some error, the first eigenvalues of the Laplacian $\\Delta$ on $M$ as well as the corresponding eigenfunctions restricted on an open set in $M$. We then construct a stable approximation to the manifold $(M,g)$. Namely, we construct a metric space and a Riemannian manifold which differ, in a proper sense, just a little from $M$ when the above data are given with a small error. We give an explicit logarithmic stability estimate on how the constructed manifold and the metric on it depend on the errors in the given data. Moreover a similar stability estimate is derived for the Gel'fand's inverse problem. The proof is based on methods from geometric convergence, a quantitative stability estimate for the unique continuation and a new version of the geometric Boundary Control method

Topics & Concepts

MathematicsInverse problemStability (learning theory)InverseMathematical analysisApplied mathematicsGeometryComputer scienceMachine learningNumerical methods in inverse problemsAdvanced Mathematical Modeling in EngineeringGeometric Analysis and Curvature Flows
Reconstruction and stability in Gelfand’s inverseinterior spectral problem | Litcius