Papers
Topics
Authors
Recent
Search
2000 character limit reached

Extremal Steklov-Neumann Eigenvalues

Published 19 Sep 2025 in math.OC and math.SP | (2509.15975v1)

Abstract: Let Ω\Omega be a bounded open planar domain with smooth connected boundary, Γ\Gamma, that has been partitioned into two disjoint components, Γ=ΓS⊔ΓN\Gamma = \Gamma_S \sqcup \Gamma_N. We consider the Steklov-Neumann eigenproblem on Ω\Omega, where a harmonic function is sought that satisfies the Steklov boundary condition on ΓS\Gamma_S and the Neumann boundary condition on ΓN\Gamma_N. We pose the extremal eigenvalue problems (EEPs) of minimizing/maximizing the kk-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<sup>∞(Γ)L<sup>\infty(\Gamma) density replaces the boundary partition. For these relaxed EEPs, we establish existence, prove optimality conditions, show that the maximization problem is convex for k=1k=1 and non-convex for k≥2k\geq 2, and establish symmetry properties for the maximizing densities for k=1k=1. 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 ΓS⊔ΓN\Gamma_S\sqcup \Gamma_N for the kk-th eigenvalue consists of k+1k+1 connected components that are symmetrically arranged on the boundary. For a disk, we prove that for k=1k = 1, the constant density is a maximizer for the relaxed problem; we also provide numerical and asymptotic evidence that for k≥2k\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.

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.