Spectral isoperimetric inequalities for Robin Laplacians on 2-manifolds and unbounded cones

IF 1 3区 数学 Q1 MATHEMATICS Journal of Spectral Theory Pub Date : 2019-09-24 DOI:10.4171/jst/416
Magda Khalile, V. Lotoreichik
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引用次数: 7

Abstract

We consider the problem of geometric optimization of the lowest eigenvalue for the Laplacian on a compact, simply-connected two-dimensional manifold with boundary subject to an attractive Robin boundary condition. We prove that in the sub-class of manifolds with the Gauss curvature bounded from above by a constant $K_\circ \ge 0$ and under the constraint of fixed perimeter, the geodesic disk of constant curvature $K_\circ$ maximizes the lowest Robin eigenvalue. In the same geometric setting, it is proved that the spectral isoperimetric inequality holds for the lowest eigenvalue of the Dirichlet-to-Neumann operator. Finally, we adapt our methods to Robin Laplacians acting on unbounded three-dimensional cones to show that, under a constraint of fixed perimeter of the cross-section, the lowest Robin eigenvalue is maximized by the circular cone.
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Robin-Laplaceans在2-流形和无界锥上的谱等周不等式
我们考虑了具有吸引Robin边界条件的边界的紧致、简单连接的二维流形上拉普拉斯算子的最低特征值的几何优化问题。我们证明了在高斯曲率由常数$K_\circ0$从上界的流形的子类中,在固定周长的约束下,常曲率的测地圆盘$K_\ccirc$最大化了最低Robin特征值。在相同的几何条件下,证明了Dirichlet到Neumann算子的最低特征值的谱等周不等式成立。最后,我们将我们的方法应用于作用于无界三维锥的Robin-Laplaces,以表明在截面周长固定的约束下,最小Robin特征值由圆锥最大化。
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来源期刊
Journal of Spectral Theory
Journal of Spectral Theory MATHEMATICS, APPLIED-MATHEMATICS
CiteScore
2.00
自引率
0.00%
发文量
30
期刊介绍: The Journal of Spectral Theory is devoted to the publication of research articles that focus on spectral theory and its many areas of application. Articles of all lengths including surveys of parts of the subject are very welcome. The following list includes several aspects of spectral theory and also fields which feature substantial applications of (or to) spectral theory. Schrödinger operators, scattering theory and resonances; eigenvalues: perturbation theory, asymptotics and inequalities; quantum graphs, graph Laplacians; pseudo-differential operators and semi-classical analysis; random matrix theory; the Anderson model and other random media; non-self-adjoint matrices and operators, including Toeplitz operators; spectral geometry, including manifolds and automorphic forms; linear and nonlinear differential operators, especially those arising in geometry and physics; orthogonal polynomials; inverse problems.
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