Quadrature Points via Heat Kernel Repulsion

Jianfeng Lu, Matthias Sachs*, Stefan Steinerberger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

We discuss the classical problem of how to pick N weighted points on a d-dimensional manifold so as to obtain a reasonable quadrature rule 1|M|∫Mf(x)dx≃∑n=1Naif(xi).This problem, naturally, has a long history; the purpose of our paper is to propose selecting points and weights so as to minimize the energy functional ∑i,j=1Naiajexp(-d(xi,xj)24t)→min,wheret∼N-2/d,d(x, y) is the geodesic distance, and d is the dimension of the manifold. This yields point sets that are theoretically guaranteed, via spectral theoretic properties of the Laplacian - Δ , to have good properties. One nice aspect is that the energy functional is universal and independent of the underlying manifold; we show several numerical examples.

Original languageEnglish
Pages (from-to)27-48
Number of pages22
JournalConstructive Approximation
Volume51
Issue number1
DOIs
Publication statusPublished - 1 Feb 2020

Bibliographical note

Funding Information:
This work was partially supported by the National Science Foundation under Grant DMS-1638521 to the Statistical and Applied Mathematical Sciences Institute. The research of J.L. was also supported in part by the National Science Foundation under award DMS-1454939.

Publisher Copyright:
© 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords

  • Heat kernel
  • Numerical Integration
  • Quadrature

ASJC Scopus subject areas

  • Analysis
  • General Mathematics
  • Computational Mathematics

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