Shape optimization for the Laplacian eigenvalue over triangles and its application to interpolation error constant estimation

R Endo, X Liu�- arXiv preprint arXiv:2209.13415, 2022 - arxiv.org
arXiv preprint arXiv:2209.13415, 2022arxiv.org
A computer-assisted proof is proposed for the Laplacian eigenvalue minimization problems
over triangular domains under diameter constraints. The proof utilizes recently developed
guaranteed computation methods for both eigenvalues and eigenfunctions of differential
operators. The paper also provides an elementary and concise proof of the Hadamard
shape derivative, which helps to validate the monotonicity of eigenvalue with respect to
shape parameters. Besides the model homogeneous Dirichlet eigenvalue problem, the�…
A computer-assisted proof is proposed for the Laplacian eigenvalue minimization problems over triangular domains under diameter constraints. The proof utilizes recently developed guaranteed computation methods for both eigenvalues and eigenfunctions of differential operators. The paper also provides an elementary and concise proof of the Hadamard shape derivative, which helps to validate the monotonicity of eigenvalue with respect to shape parameters. Besides the model homogeneous Dirichlet eigenvalue problem, the eigenvalue problem associated with a non-homogeneous Neumann boundary condition, which is related to the Crouzeix--Raviart interpolation error constant, is considered. The computer-assisted proof tells that among the triangles with the unit diameter, the equilateral triangle minimizes the first eigenvalue for each concerned eigenvalue problem.
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