nifty-ls: Fast and Accurate Lomb–Scargle Periodograms Using a Non-uniform FFT

Abstract We present nifty-ls , a software package for fast and accurate evaluation of the Lomb–Scargle periodogram. nifty-ls leverages the fact that Lomb–Scargle can be computed using a non-uniform fast Fourier transform (NUFFT), which we evaluate with the Flatiron Institute NUFFT package ( finufft ). This approach achieves a many-fold speedup over the Press & Rybicki method as implemented in Astropy and is simultaneously many orders of magnitude more accurate. nifty-ls also supports fast evaluation on GPUs via CUDA and integrates with the Astropy Lomb–Scargle interface. nifty-ls is publicly available at https://github.com/flatironinstitute/nifty-ls/ .

Authors

Publication Details

Journal
Research Notes of the AAS
Published
2024-10-04
DOI
https://doi.org/10.3847/2515-5172/ad82cd
Citations
5
Primary Topic
Matrix Theory and Algorithms
Type
article
Field-Weighted Citation Impact
1.81
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article

nifty-ls: Fast and Accurate Lomb–Scargle Periodograms Using a Non-uniform FFT

Yu-hsuan Shih, Daniel Foreman-Mackey, Lehman H. Garrison, Alex H. Barnett
5 citations
Research Notes of the AAS
Matrix Theory and Algorithms
1.81
article

nifty-ls: Fast and Accurate Lomb–Scargle Periodograms Using a Non-uniform FFT

Yu-hsuan Shih, Daniel Foreman-Mackey, Lehman H. Garrison, Alex H. Barnett
article en
5 citations

Abstract

Abstract We present nifty-ls , a software package for fast and accurate evaluation of the Lomb–Scargle periodogram. nifty-ls leverages the fact that Lomb–Scargle can be computed using a non-uniform fast Fourier transform (NUFFT), which we evaluate with the Flatiron Institute NUFFT package ( finufft ). This approach achieves a many-fold speedup over the Press & Rybicki method as implemented in Astropy and is simultaneously many orders of magnitude more accurate. nifty-ls also supports fast evaluation on GPUs via CUDA and integrates with the Astropy Lomb–Scargle interface. nifty-ls is publicly available at https://github.com/flatironinstitute/nifty-ls/ .

Research Notes of the AASVol. 8(10)
Openalex Percentile: Top 13%
Matrix Theory and Algorithms
1.81
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nifty-ls: Fast and Accurate Lomb–Scargle Periodograms Using a Non-uniform FFT — Yu-hsuan Shih, Daniel Foreman-Mackey, et al. · Research Notes of the AAS (2024) | TGRS Research Map | TGRS