Inverse Scattering Theory and Transmission Eigenvalues - Inria - Institut national de recherche en sciences et technologies du numérique
Books Year : 2022

Inverse Scattering Theory and Transmission Eigenvalues

Abstract

In the first edition of this book, we discussed methods for determining the support of an inhomogeneous media from measured far field data as well as an extensive study of the central role played by the transmission eigenvalue problem in the mathematical development of these methods. In particular, we introduced the generalized linear sampling method (GLSM) and showed that this method provides a mathematical explanation of why it is permissible to use Tikhonov regularization to obtain an approximate solution of the far field equation associated with the linear sampling method. In the five years since the first edition of our book appeared, there has been considerable progress in both the development of GLSM as well as the theory of transmission eigenvalues. In this second edition, in addition to correcting typos in the first edition, we have added several highlights taken from these new developments. In particular, we have included new chapters on 1) the use of modified background media in the nondestructive testing of materials and in particular methods for determining the modified transmission eigenvalues that arise in such applications from measured far field data, 2) a study of a subset of transmission eigenvalues, called non-scattering wave numbers, through the use of techniques taken from the theory of free boundary value problems for elliptic partial differential equations and 3) the duality between scattering poles and transmission eigenvalues which, in addition to their intrinsic mathematical interest, leads to new methods for the numerical computation of scattering poles.
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Dates and versions

hal-03899457 , version 1 (14-12-2022)

Identifiers

  • HAL Id : hal-03899457 , version 1

Cite

Fioralba Cakoni, David Colton, Houssem Haddar. Inverse Scattering Theory and Transmission Eigenvalues. CBMS-NSF, 98, 2022, 978-1611977417. ⟨hal-03899457⟩
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