English

Elastic Calder\'on Problem via Resonant Hard Inclusions: Linearisation of the N-D Map and Density Reconstruction

Analysis of PDEs 2026-01-19 v1 Mathematical Physics math.MP

Abstract

We study an elastic Calderon-type inverse problem: recover the mass density ρ(x)\rho(x) in a bounded domain ΩR3\Omega\subset\mathbb{R}^3 from the Neumann-to-Dirichlet map associated with the isotropic Lam\'e system Lλ,μu+ω2ρ(x)u=0\mathcal{L}_{\lambda,\mu}u+\omega^2\rho(x)u=0. We introduce a constructive strategy that embeds a subwavelength periodic array of resonant high-density (hard) inclusions to create an effective medium with a uniform negative density shift. Specifically, we place a periodic cluster of inclusions of size aa and density ρ1a2\rho_1\asymp a^{-2} strictly inside Ω\Omega. For frequencies ω\omega tuned to an eigenvalue of the elastic Newton (Kelvin) operator of a single inclusion, we show that as a0a\to0 and the number of inclusions MM\to\infty, the Neumann-to-Dirichlet map ΛD\Lambda_D converges to an effective map ΛP\Lambda_{\mathcal{P}} corresponding to a background density shift P2-\mathcal{P}^2, with the operator norm estimate ΛDΛPCaαP6\|\Lambda_D-\Lambda_{\mathcal{P}}\|\le Ca^{\alpha}\mathcal{P}^6 for some α>0\alpha>0 determined by the geometric scaling. Around this negative background we derive a first-order linearization of ΛP\Lambda_{\mathcal{P}} in terms of ρ\rho and the Newton volume potential for the shifted Lam\'e operator. Testing the linearized relation with complex geometric optics solutions yields an explicit reconstruction formula for the Fourier transform of ρ\rho, and hence a global density recovery scheme. The results provide a metamaterial-inspired analytic framework for inverse coefficient problems in linear elasticity and a concrete paradigm for leveraging nanoscale resonators in reconstruction algorithms.

Keywords

Cite

@article{arxiv.2601.11356,
  title  = {Elastic Calder\'on Problem via Resonant Hard Inclusions: Linearisation of the N-D Map and Density Reconstruction},
  author = {Huaian Diao and Mourad Sini and Ruixiang Tang},
  journal= {arXiv preprint arXiv:2601.11356},
  year   = {2026}
}