Hessian Estimates for Dirichlet and Neumann Eigenfunctions of Laplacian

Abstract By methods of stochastic analysis on Riemannian manifolds, we develop an approach to determine an explicit constant $c(D)$ for an $n$-dimensional compact manifold $D$ with smooth boundary such that $\frac{\lambda }{n}\,\|\phi \|_{\infty } \leq \|\operatorname{Hess}\phi \|_{\infty } \leq c(D)\lambda \,\|\phi \|_{\infty } $ holds for any Dirichlet eigenfunction $\phi $ of $-\Delta $ on $D$ with eigenvalue $\lambda $. Our results provide the sharp Hessian estimate $\|\operatorname{Hess} \phi \|_{\infty }\lesssim \lambda ^{\frac{n+3}{4}}\|\phi \|_{L^{2}}$. Corresponding Hessian estimates for Neumann eigenfunctions are derived in the second part of the paper.

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Publication Details

Journal
International Mathematics Research Notices
Published
2024-09-30
DOI
https://doi.org/10.1093/imrn/rnae207
Primary Topic
Advanced Mathematical Modeling in Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Hessian Estimates for Dirichlet and Neumann Eigenfunctions of Laplacian

Feng‐Yu Wang, Anton Thalmaier, Li-Juan Cheng
International Mathematics Research Notices
Advanced Mathematical Modeling in Engineering
article

Hessian Estimates for Dirichlet and Neumann Eigenfunctions of Laplacian

Feng‐Yu Wang, Anton Thalmaier, Li-Juan Cheng
article en

Abstract

Abstract By methods of stochastic analysis on Riemannian manifolds, we develop an approach to determine an explicit constant $c(D)$ for an $n$-dimensional compact manifold $D$ with smooth boundary such that $\frac{\lambda }{n}\,\|\phi \|_{\infty } \leq \|\operatorname{Hess}\phi \|_{\infty } \leq c(D)\lambda \,\|\phi \|_{\infty } $ holds for any Dirichlet eigenfunction $\phi $ of $-\Delta $ on $D$ with eigenvalue $\lambda $. Our results provide the sharp Hessian estimate $\|\operatorname{Hess} \phi \|_{\infty }\lesssim \lambda ^{\frac{n+3}{4}}\|\phi \|_{L^{2}}$. Corresponding Hessian estimates for Neumann eigenfunctions are derived in the second part of the paper.

International Mathematics Research NoticesVol. 2024(21)
Tianjin University (CN), Hangzhou Normal University (CN), University of Luxembourg (LU)
National Natural Science Foundation of China, National Key Research and Development Program of China, Natural Science Foundation of Zhejiang Province
Openalex Percentile: Top 80%
Advanced Mathematical Modeling in Engineering
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