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Shape reconstructions by using plasmon resonances

  • Ming-Hui Ding
  • , Hongyu Liu*
  • , Guang-Hui Zheng*
  • *Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

99 Downloads (CityUHK Scholars)

Abstract

We study the shape reconstruction of an inclusion from the faraway measurement of the associated electric field. This is an inverse problem of practical importance in biomedical imaging and is known to be notoriously ill-posed. By incorporating Drudeâ' model of the permittivity parameter, we propose a novel reconstruction scheme by using the plasmon resonance with a significantly enhanced resonant field. We conduct a delicate sensitivity analysis to establish a sharp relationship between the sensitivity of the reconstruction and the plasmon resonance. It is shown that when plasmon resonance occurs, the sensitivity functional blows up and hence ensures a more robust and effective construction. Then we combine the Tikhonov regularization with the Laplace approximation to solve the inverse problem, which is an organic hybridization of the deterministic and stochastic methods and can quickly calculate the minimizer while capture the uncertainty of the solution. We conduct extensive numerical experiments to illustrate the promising features of the proposed reconstruction scheme.
Original languageEnglish
Pages (from-to)705-726
JournalESAIM: Mathematical Modelling and Numerical Analysis
Volume56
Issue number2
Online published15 Mar 2022
DOIs
Publication statusPublished - Mar 2022

Funding

The work of M Ding and G Zheng were supported by the NSF of China (11301168) and NSF of Hunan (2020JJ4166) and NSF Innovation Platform Open Fund project of Hunan Province No. 20K030. The work of H Liu was supported by the Hong Kong RGC General Research Fund (projects 12302919, 12301218 and 11300821) and the NSFC/RGC Joint Research Grant (project N CityU101/21).

Research Keywords

  • Laplace approximation
  • Plasmon resonance
  • Sensitivity analysis
  • Shape reconstruction
  • Tikhonov regularization

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

RGC Funding Information

  • RGC-funded

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