A convex lifting approach for the Calderón problem

Fuente: arXiv
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Main Authors: Alberti, Giovanni S., Petit, Romain, Sanna, Simone
Format: Preprint
Published: 2025
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author Alberti, Giovanni S.
Petit, Romain
Sanna, Simone
author_facet Alberti, Giovanni S.
Petit, Romain
Sanna, Simone
contents The Calderón problem consists in recovering an unknown coefficient of a partial differential equation from boundary measurements of its solution. These measurements give rise to a highly nonlinear forward operator. As a consequence, the development of reconstruction methods for this inverse problem is challenging, as they usually suffer from the problem of local convergence. To circumvent this issue, we propose an alternative approach based on lifting and convex relaxation techniques, that have been successfully developed for solving finite-dimensional quadratic inverse problems. This leads to a convex optimization problem whose solution coincides with the sought-after coefficient, provided that a non-degenerate source condition holds. We demonstrate the validity of our approach on a toy model where the solution of the partial differential equation is known everywhere in the domain. In this simplified setting, we verify that the non-degenerate source condition holds under certain assumptions on the unknown coefficient. We leave the investigation of its validity in the Calderón setting for future works.
format Preprint
id arxiv_https___arxiv_org_abs_2507_00645
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A convex lifting approach for the Calderón problem
Alberti, Giovanni S.
Petit, Romain
Sanna, Simone
Analysis of PDEs
Numerical Analysis
Functional Analysis
Optimization and Control
The Calderón problem consists in recovering an unknown coefficient of a partial differential equation from boundary measurements of its solution. These measurements give rise to a highly nonlinear forward operator. As a consequence, the development of reconstruction methods for this inverse problem is challenging, as they usually suffer from the problem of local convergence. To circumvent this issue, we propose an alternative approach based on lifting and convex relaxation techniques, that have been successfully developed for solving finite-dimensional quadratic inverse problems. This leads to a convex optimization problem whose solution coincides with the sought-after coefficient, provided that a non-degenerate source condition holds. We demonstrate the validity of our approach on a toy model where the solution of the partial differential equation is known everywhere in the domain. In this simplified setting, we verify that the non-degenerate source condition holds under certain assumptions on the unknown coefficient. We leave the investigation of its validity in the Calderón setting for future works.
title A convex lifting approach for the Calderón problem
topic Analysis of PDEs
Numerical Analysis
Functional Analysis
Optimization and Control
url https://arxiv.org/abs/2507.00645