English

Miminization of the first eigenvalue of the Dirichlet Laplacian with a small volume obstacle

Analysis of PDEs 2025-07-28 v1

Abstract

We consider the well-known shape optimization problem with spectral cost: minimizing the first eigenvalue of the Dirichlet Laplacian among all subdomains Ω\Omega having prescribed volume and contained in a fixed box DD; equivalently, we look for the best way to remove a compact set (obstacle) KDK\subset\overline{D} of Lebesgue measure K=ε|K|=\varepsilon, 0<ε<D0<\varepsilon<|D|, in order to minimize the first Dirichlet eigenvalue of the set Ω=DK\Omega = D \setminus K. In the small volume regime ε0\varepsilon\to0, we prove that the optimal obstacles accumulate, in a suitable sense, to points of D\partial D where ϕ0|\nabla \phi_0| is minimal, where ϕ0\phi_0 denotes the first eigenfunction of the Dirichlet Laplacian on DD. Moreover, we provide a fairly detailed description of the convergence of the optimal eigenvalues, eigenfunctions and free boundaries. Our results are based on sharp estimates of the optimal eigenvalues, in terms of a suitable notion of relative capacity.

Keywords

Cite

@article{arxiv.2507.19339,
  title  = {Miminization of the first eigenvalue of the Dirichlet Laplacian with a small volume obstacle},
  author = {Benedetta Noris and Giovanni Siclari and Gianmaria Verzini},
  journal= {arXiv preprint arXiv:2507.19339},
  year   = {2025}
}

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25 pages