A comparison of period finding algorithms
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}
}
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.
July 12, 2013 by hgpu
