Approximation of the inverse scattering Steklov eigenvalues and the inverse spectral problem

In this paper, we consider the numerical approximation of the Steklov eigenvalue problem that arises in inverse acoustic scattering. The underlying scattering problem is for an inhomogeneous isotropic medium. These eigenvalues have been proposed to be used as a target signature since they can be recovered from the scattering data. A Galerkin method is studied where the basis functions are the Neumann eigenfunctions of the Laplacian. Error estimates for the eigenvalues and eigenfunctions are proven by appealing to Weyl's law. We will test this method against separation of variables in order to validate the theoretical convergence. We also consider the inverse spectral problem of estimating/recovering the refractive index from the knowledge of the Steklov eigenvalues, since the eigenvalues are monotone with respect to a real-valued refractive index implying that they can be used for nondestructive testing. Some numerical examples are provided for the inverse spectral problem.

Automated summary

This paper discusses the numerical approximation of the Steklov eigenvalue problem in inverse acoustic scattering, focusing on the Galerkin method using Neumann eigenfunctions of the Laplacian as basis functions. Error estimates are proven and the method is tested against separation of variables for validation. The inverse spectral problem of estimating/refractive index from Steklov eigenvalues is also considered, with numerical examples provided.