拉普拉斯-贝尔特拉米特征函数中更高的特征切格比

IF 2.6 2区 数学 Q1 MATHEMATICS, APPLIED
Gary Froyland, Christopher P. Rock
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引用次数: 0

摘要

本文研究了拉普拉斯-贝尔特拉米算子的特征值和特征函数与光滑黎曼流形(可能是加权流形和/或有边界流形)的高Cheeger常数之间的联系。高阶切格常数给出了流形主要几何特征的松散描述。我们根据任何特征函数的特征值与相应的节点域数,给出了高阶切格常数的构造上界。具体地说,我们证明了对于每一个这样的特征函数,其超水平集合的正量度集合的切格比在相应的特征值上都有上界。有些流形的主要特征缠绕在多个特征函数上,没有一个特征函数包含所有主要特征。在这种情况下,可能存在精心选择的特征函数线性组合,每个特征函数在单个特征上的值较大,而在其他特征上的值较小。然后,我们可以对这些线性组合应用软阈值算子,得到新的函数,每个函数都支持一个特征。我们证明,这些函数的水平集的切格比也给出了拉普拉斯-贝尔特拉米特征值的上限。我们将这些水平集结果扩展到非自主动态系统,并证明动态拉普拉斯特征函数揭示了具有较小动态切格比的水平集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Higher Cheeger ratios of features in Laplace-Beltrami eigenfunctions
This paper investigates links between the eigenvalues and eigenfunctions of the Laplace-Beltrami operator, and the higher Cheeger constants of smooth Riemannian manifolds, possibly weighted and/or with boundary. The higher Cheeger constants give a loose description of the major geometric features of a manifold. We give a constructive upper bound on the higher Cheeger constants, in terms of the eigenvalue of any eigenfunction with the corresponding number of nodal domains. Specifically, we show that for each such eigenfunction, a positive-measure collection of its superlevel sets have their Cheeger ratios bounded above in terms of the corresponding eigenvalue.
Some manifolds have their major features entwined across several eigenfunctions, and no single eigenfunction contains all the major features. In this case, there may exist carefully chosen linear combinations of the eigenfunctions, each with large values on a single feature, and small values elsewhere. We can then apply a soft-thresholding operator to these linear combinations to obtain new functions, each supported on a single feature. We show that the Cheeger ratios of the level sets of these functions also give an upper bound on the Laplace-Beltrami eigenvalues. We extend these level set results to nonautonomous dynamical systems, and show that the dynamic Laplacian eigenfunctions reveal sets with small dynamic Cheeger ratios.
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来源期刊
Applied and Computational Harmonic Analysis
Applied and Computational Harmonic Analysis 物理-物理:数学物理
CiteScore
5.40
自引率
4.00%
发文量
67
审稿时长
22.9 weeks
期刊介绍: Applied and Computational Harmonic Analysis (ACHA) is an interdisciplinary journal that publishes high-quality papers in all areas of mathematical sciences related to the applied and computational aspects of harmonic analysis, with special emphasis on innovative theoretical development, methods, and algorithms, for information processing, manipulation, understanding, and so forth. The objectives of the journal are to chronicle the important publications in the rapidly growing field of data representation and analysis, to stimulate research in relevant interdisciplinary areas, and to provide a common link among mathematical, physical, and life scientists, as well as engineers.
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