Mikyoung Lim

Enhancement of Near Cloaking Using Generalized Polarization Tensors Vanishing Structures. Part I: The Conductivity Problem

The aim of this paper is to provide an original method of constructing very effective near-cloaking structures for the conductivity problem. These new structures are such that their first Generalized Polarization Tensors (GPT) vanish. We show that this in particular significantly enhances the cloaking effect. We then present some numerical examples of Generalized Polarization Tensors vanishing structures.

Mathematical and statistical methods for multistatic imaging

Mathematical and Probabilistic Tools.- Small Volume Expansions and Concept of Generalized Polarization Tensors.- Multistatic Configuration.- Localization and Detection Algorithms.- Dictionary Matching and Tracking Algorithms.- Imaging of Extended Targets.- Invisibility.- Numerical Implementations and Results.- References.- Index.

Multistatic Imaging of Extended Targets

In this paper we develop iterative approaches for imaging extended inclusions from multistatic response measurements at single or multiple frequencies. Assuming measurement noise, we perform a detailed stability and resolution analysis of the proposed algorithms in two different asymptotic regimes. We consider both the Born approximation in the nonmagnetic case and a high-frequency regime in the general case. Based on a high-frequency asymptotic analysis of the measurements, an algorithm for finding a good initial guess for the illuminated part of the inclusion is provided and its optimality is shown. The initial guess, obtained through standard statistical arguments, turns out to be Kirchhoff migration. We illustrate the efficiency and the limitations of the proposed algorithms with a variety of numerical examples.

Reconstruction of Closely Spaced Small Inclusions

In this paper we establish an explicit asymptotic formula for the steady state voltage perturbations caused by closely spaced small conductivity inhomogeneities. Based on this new formula we design a very effective numerical method to identify the location and some geometric features of these inhomogeneities from a finite number of boundary measurements. The viability of our approach is documented by numerical examples.

The generalized polarization tensors for resolved imaging. Part I: Shape reconstruction of a conductivity inclusion

With each Lipschitz domain and material parameter, an infinite number of tensors, called the Generalized Polarization Tensors (GPTs), is associated. The GPTs contain significant information on the shape of the domain and its material parameter. They generalize the concept of Polarization Tensor (PT), which can be seen as the first-order GPT. It is known that given an arbitrary shape, one can find an equivalent ellipse or ellipsoid with the same PT. In this paper we consider the problem of recovering finer details of the shape of a given domain using higher-order polarization tensors. We design an optimization approach which solves the problem by minimizing a weighted discrepancy functional. In order to compute the shape derivative of this functional, we rigorously derive an asymptotic expansion of the perturbations of the GPTs that are due to a small deformation of the boundary of the domain. Our derivations are based on the theory of layer potentials. We perform some numerical experiments to demonstrate the validity and the limitations of the proposed method. The results clearly show that our approach is very promising in recovering fine shape details. Mathematics Subject Classification (MSC2000): 35R30, 35B30

Enhancement of near cloaking for the full Maxwell equations

Recently published methods for the quasi-static limit of the Helmholtz equation is extended to consider near cloaking for the full Maxwell equations. Effective near cloaking structures are described for the electromagnetic scattering problem at a fixed frequency. These structures are, prior to using the transformation optics, layered structures designed so that their first scattering coefficients vanish. As a result, any target inside the cloaking region has near-zero scattering cross section for a band of frequencies. Analytical results show that this construction significantly enhances the cloaking effect for the full Maxwell equations.

Conductivity interface problems. Part I: Small perturbations of an interface

We derive high-order terms in the asymptotic expansions of boundary perturbations of steady-state voltage potentials resulting from small perturbations of the shape of a conductivity inclusion with C 2 -boundary. Our derivation is rigorous and based on layer potential techniques. The asymptotic expansion in this paper is valid for C 1 -perturbations and inclusions with extreme conductivities. It extends those already derived for small volume conductivity inclusions and leads us to very effective algorithms for determining lower-order Fourier coefficients of the shape perturbation of the inclusion based on boundary measurements. We perform some numerical experiments using the algorithm to test its effectiveness.

Generalized polarization tensors for shape description

With each domain, an infinite number of tensors, called the Generalized Polarization Tensors (GPTs), is associated. The GPTs contain significant information on the shape of the domain. In the recent paper (Ammari et al. in Math. Comput. 81, 367–386, 2012), a recursive optimal control scheme to recover fine shape details of a given domain using GPTs is proposed. In this paper, we show that the GPTs can be used for shape description. We also show that high-frequency oscillations of the boundary of a domain are only contained in its high-order GPTs. Indeed, we provide an original stability and resolution analysis for the reconstruction of small shape changes from the GPTs. By developing a level set version of the recursive optimization scheme, we make the change of topology possible and show that the GPTs can capture the topology of the domain. We also propose an indicator of topology which could be used in some particular cases to test whether we have the correct number of connected components in the reconstructed image. We provide analytical and numerical evidence that GPTs can capture topology and high-frequency shape oscillations. The results of this paper clearly show that the concept of GPTs is a very promising new tool for shape description.

Blow-up of Electric Fields between Closely Spaced Spherical Perfect Conductors

The electric field increases toward infinity in the narrow region between closely adjacent perfect conductors as they approach each other. Much attention has been devoted to the blow-up estimate, especially in two dimensions, for the practical relevance to high stress concentration in fiber-reinforced elastic composites. In this paper, we establish optimal estimates for the electric field associated with the distance between two spherical conductors in n-dimensional spaces for n ≥ 2. The novelty of these estimates is that they explicitly describe the dependency of the blow-up rate on the geometric parameters: the radii of the conductors.

A New Optimal Control Approach for the Reconstruction of Extended Inclusions

The aim of this paper is to propose a new regularized optimal control formulation for recovering an extended inclusion from boundary measurements. Our approach provides an optimal representation of the shape of the inclusion. It guarantees local Lipschitz stability for the reconstruction problem. Some numerical experiments are performed to demonstrate the validity and the limitations of the proposed reconstruction method.