When surface evolution meets Fokker-Planck equation: a novel tangential velocity model for uniform parametrization

A common issue in simulating geometric evolution of surfaces is unexpected clustering of points that may cause numerical instability. We propose a novel artificial tangential velocity method for this matter. The artificial tangential velocity is generated from a surface density field governed by a Fokker-Planck equation to guide the point distribution. A target distribution matching algorithm is developed leveraging the surface Kullback-Leibler divergence of density functions. The numerical method is formulated within a fully meshless framework using the moving least squares approximation, thereby eliminating the need for mesh generation and allowing flexible treatment of unstructured point cloud data. Extensive numerical experiments are conducted to demonstrate the robustness, accuracy, and effectiveness of the proposed approach across a variety of surface evolution problems, including the mean curvature flow.

Publication Details

Journal
ArXiv.org
Published
2025-07-11
Primary Topic
Computational Geometry and Mesh Generation
Type
article
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article

When surface evolution meets Fokker-Planck equation: a novel tangential velocity model for uniform parametrization

ArXiv.org
Computational Geometry and Mesh Generation
article

When surface evolution meets Fokker-Planck equation: a novel tangential velocity model for uniform parametrization

article en

Abstract

A common issue in simulating geometric evolution of surfaces is unexpected clustering of points that may cause numerical instability. We propose a novel artificial tangential velocity method for this matter. The artificial tangential velocity is generated from a surface density field governed by a Fokker-Planck equation to guide the point distribution. A target distribution matching algorithm is developed leveraging the surface Kullback-Leibler divergence of density functions. The numerical method is formulated within a fully meshless framework using the moving least squares approximation, thereby eliminating the need for mesh generation and allowing flexible treatment of unstructured point cloud data. Extensive numerical experiments are conducted to demonstrate the robustness, accuracy, and effectiveness of the proposed approach across a variety of surface evolution problems, including the mean curvature flow.

ArXiv.org
Openalex Percentile: Top 33%
Computational Geometry and Mesh Generation
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