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Manifold parametrizations by eigenfunctions of the Laplacian and heat kernels

  • Yale University
  • Duke University

Research output: Contribution to journalArticlepeer-review

115 Scopus citations

Abstract

We use heat kernels or eigenfunctions of the Laplacian to construct local coordinates on large classes of Euclidean domains and Riemannian manifolds (not necessarily smooth, e.g., with Cα metric). These coordinates are bi-Lipschitz on large neighborhoods of the domain or manifold, with constants controlling the distortion and the size of the neighborhoods that depend only on natural geometric properties of the domain or manifold. The proof of these results relies on novel estimates, from above and below, for the heat kernel and its gradient, as well as for the eigenfunctions of the Laplacian and their gradient, that hold in the non-smooth category, and are stable with respect to perturbations within this category. Finally, these coordinate systems are intrinsic and efficiently computable, and are of value in applications.

Original languageEnglish
Pages (from-to)1803-1808
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume105
Issue number6
DOIs
StatePublished - Feb 12 2008

Keywords

  • Nonlinear dimensionality reduction
  • Spectral geometry

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