9943

A comparison of period finding algorithms

Matthew J. Graham, Andrew J. Drake, S.G. Djorgovski, Ashish A. Mahabal, Ciro Donalek, Victor Duan, Alison Maher
California Institute of Technology, 1200 E. California Blvd, Pasadena, CA 91125, USA
arXiv:1307.2209 [astro-ph.IM], (8 Jul 2013)

@article{2013arXiv1307.2209G,

   author={Graham}, M.~J. and {Drake}, A.~J. and {Djorgovski}, S.~G. and {Mahabal}, A.~A. and {Donalek}, C. and {Duan}, V. and {Maher}, A.},

   title={"{A comparison of period finding algorithms}"},

   journal={ArXiv e-prints},

   archivePrefix={"arXiv"},

   eprint={1307.2209},

   primaryClass={"astro-ph.IM"},

   keywords={Astrophysics – Instrumentation and Methods for Astrophysics},

   year={2013},

   month={jul},

   adsurl={http://adsabs.harvard.edu/abs/2013arXiv1307.2209G},

   adsnote={Provided by the SAO/NASA Astrophysics Data System}

}

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This paper presents a comparison of popular period finding algorithms applied to the light curves of variable stars from the Catalina Real-time Transient Survey (CRTS), MACHO and ASAS data sets. We analyze the accuracy of the methods against magnitude, sampling rates, quoted period, quality measures (signal-to-noise and number of observations), variability, and object classes. We find that measure of dispersion-based techniques – analysis-of-variance with harmonics and conditional entropy – consistently give the best results but there are clear dependencies on object class and light curve quality. Period aliasing and identifying a period harmonic also remain significant issues. We consider the performance of the algorithms and show that a new conditional entropy-based algorithm is the most optimal in terms of completeness and speed. We also consider a simple ensemble approach and find that it performs no better than individual algorithms.
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