2012
DOI: 10.1007/s00220-012-1615-8
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Enhancement of Near Cloaking Using Generalized Polarization Tensors Vanishing Structures. Part I: The Conductivity Problem

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

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Cited by 102 publications
(137 citation statements)
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“…We refer to [6] and references therein for these applications. It is worth mentioning that the notion of GPTs has been used not only for imaging but also for invisibility cloaking [7].…”
Section: Introductionmentioning
confidence: 99%
“…We refer to [6] and references therein for these applications. It is worth mentioning that the notion of GPTs has been used not only for imaging but also for invisibility cloaking [7].…”
Section: Introductionmentioning
confidence: 99%
“…Expansion (2.14) is valid if |x| → ∞ and y ∈ ∂B. The contracted generalized polarization tensors are defined as follows (see [12]): …”
Section: Contracted Gpts and Asymptotic Expansionsmentioning
confidence: 99%
“…Recently the concept of GPTs finds another promising application to cloaking and electromagnetic and acoustic invisibility. It is shown that the near-cloaking effect of [29] can be dramatically improved by using multi-layered structures whose GPTs vanish up to a certain order [12].…”
Section: Introductionmentioning
confidence: 99%
“…Along another seemingly unrelated research line, Ammari et al (2011) constructed very effective near-cloaking multicoated structures for conductivity problem (or mathematically equivalent anti-plane shear problem). The first generalized polarization tensors vanish in their designed near-cloaking structures, and thus these structures are made neutral to remote nonuniform loading of general type.…”
Section: Introductionmentioning
confidence: 99%