Stable reconstruction of simple Riemannian manifolds from unknown interior sources

Abstract
Consider the geometric inverse problem: there is a set of delta-sources in spacetime that emit waves travelling at unit speed. If we know all the arrival times at the boundary cylinder of the spacetime, can we reconstruct the space, a Riemannian manifold with boundary? With a finite set of sources we can only hope to get an approximate reconstruction, and we indeed provide a discrete metric approximation to the manifold with explicit data-driven error bounds when the manifold is simple. This is the geometrization of a seismological inverse problem where we measure the arrival times on the surface of waves from an unknown number of unknown interior microseismic events at unknown times. The closeness of two metric spaces with a marked boundary is measured by a labeled Gromov–Hausdorff distance. If measurements are done for infinite time and spatially dense sources, our construction produces the true Riemannian manifold and the finite-time approximations converge to it in the metric sense
Main Authors
Format
Articles Research article
Published
2023
Series
Subjects
Publication in research information system
Publisher
IOP Publishing
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202308304827Use this for linking
Review status
Peer reviewed
ISSN
0266-5611
DOI
https://doi.org/10.1088/1361-6420/ace6c9
Language
English
Published in
Inverse Problems
Citation
  • de Hoop, M. V., Ilmavirta, J., Lassas, M., & Saksala, T. (2023). Stable reconstruction of simple Riemannian manifolds from unknown interior sources. Inverse Problems, 39(9), Article 095002. https://doi.org/10.1088/1361-6420/ace6c9
License
CC BY 4.0Open Access
Funder(s)
Research Council of Finland
Funding program(s)
Centre of Excellence, AoF
Huippuyksikkörahoitus, SA
Research Council of Finland
Additional information about funding
M V d H was supported by the Simons Foundation under the MATH + X program, the National Science Foundation under Grant DMS-1815143, and the corporate members of the Geo-Mathematical Imaging Group at Rice University. J I was supported by the Academy of Finland (Projects 332890 and 336254). M L was supported by Academy of Finland (Projects 284715 and 303754). T S was supported by the Simons Foundation under the MATH + X program and the corporate members of the Geo-Mathematical Imaging Group at Rice University.
Copyright© 2023 The Author(s). Published by IOP Publishing Ltd Printed in the UK

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