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Fast algorithm for spectral analysis of unevenly sampled data
Abstract
The Lomb-Scargle method performs spectral analysis on unevenly sampled data and is known to be a powerful way to find, and test the significance of, weak periodic signals. The method has previously been thought to be 'slow', requiring of order 10(2)N(2) operations to analyze N data points. We show that Fast Fourier Transforms (FFTs) can be used in a novel way to make the computation of order 10(2)N log N. Despite its use of the FFT, the algorithm is in no way equivalent to conventional FFT periodogram analysis.
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Cited by
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Blum, I. D., Zhu, L., Moquin, L., Kokoeva, M. V., Gratton, A., Giros, B., & Storch, K.-F. (2014) · eLife · doi:10.7554/elife.05105 · Cited by 168
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Hartman, J. D., Gaudi, B. S., Holman, M. J., McLeod, B. A., Stanek, K. Z., Barranco, J. A., Pinsonneault, M. H., Meibom, S., & Kalirai, J. S. (2009) · The Astrophysical Journal · doi:10.1088/0004-637x/695/1/336 · Cited by 51
Metadata
- Authors
- Press, W. H., & Rybicki, G. B.
- Venue
- The Astrophysical Journal
- Publisher
- American Astronomical Society
- Published
- 1989-03
- Volume
- 338
- Pages
- 277
- ISSN
- 0004-637X (ISSN-L)
- 1538-4357
- OpenAlex
- W2008150142
- Cited by
- 772
- References
- 0
- FWCI
- 2.78
- Type
- journal article
- Language
- en
- Open access
- closed
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- Press, W. H., & Rybicki, G. B. (1989). Fast algorithm for spectral analysis of unevenly sampled data. The Astrophysical Journal. https://doi.org/10.1086/167197
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