X-ray imaging from nonlinear waves: numerical reconstruction of a cubic nonlinearity

Abstract We study an inverse boundary value problem for the nonlinear wave equation in $2 + 1$ dimensions. The objective is to recover an unknown potential $q(x, t)$ from the associated Dirichlet-to-Neumann map using real-valued waves. We propose a direct numerical reconstruction method for the Radon transform of $q$, which can then be inverted using standard X-ray tomography techniques to determine $q$. Our implementation introduces a spectral regularization procedure to stabilize the numerical differentiation step required in the reconstruction, improving robustness with respect to noise in the boundary data. We give rigorous justification and optimal stability estimates for the regularized spectral differentiation of noisy measurements, which may be of independent interest. Numerical experiments demonstrate the feasibility of recovering potentials from boundary measurements of nonlinear waves and illustrate the advantages of the Radon-based reconstruction.

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Publication Details

Journal
Inverse Problems
Published
2026-09-04
DOI
https://doi.org/10.1088/1361-6420/aea2bf
Primary Topic
Advanced X-ray Imaging Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

X-ray imaging from nonlinear waves: numerical reconstruction of a cubic nonlinearity

Teemu Tyni
Inverse Problems
Advanced X-ray Imaging Techniques
article

X-ray imaging from nonlinear waves: numerical reconstruction of a cubic nonlinearity

Teemu Tyni
article en

Abstract

Abstract We study an inverse boundary value problem for the nonlinear wave equation in $2 + 1$ dimensions. The objective is to recover an unknown potential $q(x, t)$ from the associated Dirichlet-to-Neumann map using real-valued waves. We propose a direct numerical reconstruction method for the Radon transform of $q$, which can then be inverted using standard X-ray tomography techniques to determine $q$. Our implementation introduces a spectral regularization procedure to stabilize the numerical differentiation step required in the reconstruction, improving robustness with respect to noise in the boundary data. We give rigorous justification and optimal stability estimates for the regularized spectral differentiation of noisy measurements, which may be of independent interest. Numerical experiments demonstrate the feasibility of recovering potentials from boundary measurements of nonlinear waves and illustrate the advantages of the Radon-based reconstruction.

Inverse Problems
University of Oulu (FI)
Emil Aaltosen Säätiö, Luonnontieteiden ja Tekniikan Tutkimuksen Toimikunta
Openalex Percentile: Top 99%
Advanced X-ray Imaging Techniques
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