Near-minimizers of the first Dirichlet eigenvalue of the combinatorial Laplacian on Z^d are close to a Euclidean ball: for minimizers with bounded scaled perimeter, the symmetric difference with the best ball is O_d(N^{1-1/(2d)}).
An Asymptotic Faber-Krahn Inequality for the Combinatorial Laplacian on Z^2
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abstract
The Faber-Krahn inequality states that among all open domains with a fixed volume in R^n, the ball minimizes the first Dirichlet eigenvalue of the Laplacian. We study an asymptotic discrete analogue of this for the combinatorial Dirichlet Laplacian acting on induced subgraphs of Z^2. Namely, an induced subgraph G with n vertices is called a minimizing subgraph if it minimizes the first eigenvalue of the combinatorial Dirichlet Laplacian among all induced subgraphs with n vertices. Consider an induced subgraph G and take the interior of the union of closed squares of area 1 about each point of G. Let G* denote this domain scaled down to have area 1. Our main theorem states that if {G_n} is a sequence of minimizing subgraphs where each G_n has n vertices, then after translation the measure of the symmetric difference of G_n* and the unit disk converges to 0.
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The Quantitative Faber-Krahn Inequality for the Combinatorial Laplacian in $\mathbb{Z}^{d}$
Near-minimizers of the first Dirichlet eigenvalue of the combinatorial Laplacian on Z^d are close to a Euclidean ball: for minimizers with bounded scaled perimeter, the symmetric difference with the best ball is O_d(N^{1-1/(2d)}).