Fast Expansion into Harmonics on the Disk

The dataset used in this paper is a set of L x L images representing functions on [-1, 1]^2 supported on the disk {x ∈ R^2 : |x| < 1}. The images are digitized and the authors present a fast and numerically accurate method for expanding these images into the harmonics (Dirichlet Laplacian eigenfunctions) on the disk.

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Nicholas F. Marshall, Oscar Mickelin, Amit Singer (2024). Dataset: Fast Expansion into Harmonics on the Disk. https://doi.org/10.57702/9iphe5mt

DOI retrieved: December 3, 2024

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Created December 3, 2024
Last update December 3, 2024
Defined In https://doi.org/10.48550/arXiv.2207.13674
Author Nicholas F. Marshall
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Oscar Mickelin
Amit Singer
Homepage https://doi.org/10.1002/maa.201900301