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Extremal Steklov-Neumann Eigenvalues

Chiu-Yen Kao, Braxton Osting, Chee Han Tan, Robert Viator

Abstract

Let $Ω$ be a bounded open planar domain with smooth connected boundary, $Γ$, that has been partitioned into two disjoint components, $Γ= Γ_S \sqcup Γ_N$. We consider the Steklov-Neumann eigenproblem on $Ω$, where a harmonic function is sought that satisfies the Steklov boundary condition on $Γ_S$ and the Neumann boundary condition on $Γ_N$. We pose the extremal eigenvalue problems (EEPs) of minimizing/maximizing the $k$-th non-trivial Steklov-Neumann eigenvalue among boundary partitions of prescribed measure. We formulate a relaxation of these EEPs in terms of weighted Steklov eigenvalues where an $L^\infty(Γ)$ density replaces the boundary partition. For these relaxed EEPs, we establish existence and prove optimality conditions. We also prove a homogenization result that allows us to use solutions to the relaxed EEPs to infer properties of solutions to the original EEPs. For a disk, we provide numerical and asymptotic evidence that the minimizing arrangement of $Γ_S\sqcup Γ_N$ for the $k$-th eigenvalue consists of $k+1$ connected components that are symmetrically arranged on the boundary. For a disk, for $k = 1$, the constant density is a maximizer for the relaxed problem; we also provide numerical and asymptotic evidence that for $k\ge 2$, the maximizing density for the relaxed problem is a non-trivial function; a sequence of rapidly oscillating Steklov/Neumann boundary conditions approach the supremum value.

Extremal Steklov-Neumann Eigenvalues

Abstract

Let be a bounded open planar domain with smooth connected boundary, , that has been partitioned into two disjoint components, . We consider the Steklov-Neumann eigenproblem on , where a harmonic function is sought that satisfies the Steklov boundary condition on and the Neumann boundary condition on . We pose the extremal eigenvalue problems (EEPs) of minimizing/maximizing the -th non-trivial Steklov-Neumann eigenvalue among boundary partitions of prescribed measure. We formulate a relaxation of these EEPs in terms of weighted Steklov eigenvalues where an density replaces the boundary partition. For these relaxed EEPs, we establish existence and prove optimality conditions. We also prove a homogenization result that allows us to use solutions to the relaxed EEPs to infer properties of solutions to the original EEPs. For a disk, we provide numerical and asymptotic evidence that the minimizing arrangement of for the -th eigenvalue consists of connected components that are symmetrically arranged on the boundary. For a disk, for , the constant density is a maximizer for the relaxed problem; we also provide numerical and asymptotic evidence that for , the maximizing density for the relaxed problem is a non-trivial function; a sequence of rapidly oscillating Steklov/Neumann boundary conditions approach the supremum value.

Paper Structure

This paper contains 12 sections, 8 theorems, 63 equations, 6 figures.

Key Result

Theorem 1.1

(Existence) For every $k\in \mathbb{N}$ and $\alpha \in (0,1]$, there exists $\rho_k^{\bigtriangledown} \in \mathcal{A} _\alpha$ that attains the infimum in e:RelaxMin and there exists $\rho_k^{\triangle} \in \mathcal{A} _\alpha$ that attains the supremum in e:RelaxMax.

Figures (6)

  • Figure 1: Minimizing bang-bang densities, $\rho_k^\bigtriangledown$, and associated eigenfunctions for \ref{['e:RelaxMin']} with $\Omega = \mathbb{D}$, $\alpha = 0.5$, and odd $k = 1, 3, 5, 7, 9, 11$ (values indicated). The red part of the boundary is where $\rho=1$, i.e., where the Steklov boundary condition is imposed. See Section \ref{['s:DiskMin']}.
  • Figure 2: Minimizing bang-bang densities, $\rho_k^\bigtriangledown$, and associated eigenfunctions for \ref{['e:RelaxMin']} with $\Omega = \mathbb{D}$, $\alpha = 0.5$, and even $k=2,4,12$ (values indicated). The red part of the boundary is where $\rho=1$, i.e., where the Steklov boundary condition is imposed. Each eigenvalue has multiplicity 2 and a basis for the eigenspace is plotted. See Section \ref{['s:DiskMin']}.
  • Figure 3: Solutions for \ref{['e:RelaxMin']} with $\Omega = \mathbb{D}$, $\alpha = 0.5$, and $k = 1,2,3,4$ (values indicated). In the left hand panels, the minimizing bang-bang density $\rho_k^\bigtriangledown$ is plotted in blue and the corresponding eigenfunction(s) are plotted in red. For $k$ odd, the eigenvalue is simple and the right hand panel shows that the optimality condition \ref{['e:minRhoCondMult']} is satisfied. For $k$ even, the eigenvalue has multiplicity $2$ and the right hand panel shows that the optimality condition \ref{['e:minRhoCondMult']} is satisfied for the two eigenfunctions plotted in the left hand panel. See Section \ref{['s:DiskMin']}.
  • Figure 4: (Left) Maximizing densities, $\rho_k^\triangle$, and associated eigenfunctions for \ref{['e:RelaxMax']} with $\Omega = \mathbb{D}$, $\alpha = 0.5$, and even $k=2,4,6,8$ (values indicated). Interestingly, the eigenfunctions are constant on intervals where $\rho \neq 1$. (Right) The eigenfunctions are plotted on $\Omega =\mathbb{D}$. The red part of the boundary is where $\rho=1$, i.e., where the Steklov boundary condition is imposed. See Section \ref{['s:DiskMax']}.
  • Figure 5: Solutions for \ref{['e:RelaxMax']} with $\Omega = \mathbb{D}$, $\alpha = 0.5$, and $k = 1,2,3,4$ (values indicated). In the left hand panels, the maximizing density $\rho_k^\triangle$ is plotted in blue and the corresponding eigenfunction(s) are plotted in red. For $k$ even, the eigenvalue is simple and the right hand panel shows that the optimality condition \ref{['e:maxRhoCondMult']} is satisfied. For $k$ odd, the eigenvalue has multiplicity $2$ and the right hand panel shows that the optimality condition \ref{['e:maxRhoCondMult']} is satisfied for the two eigenfunctions plotted in the left hand panel. See Section \ref{['s:DiskMax']}.
  • ...and 1 more figures

Theorems & Definitions (18)

  • Theorem 1.1
  • Remark 1.2
  • Theorem 1.3
  • Theorem 1.4
  • Definition 1.5
  • Conjecture 1.6
  • Theorem 1.7
  • Lemma 2.1: Friedland_1977
  • Lemma 2.2
  • proof
  • ...and 8 more