%0 Journal Article
%T A comparison of period finding algorithms
%A Matthew J. Graham
%A Andrew J. Drake
%A S. G. Djorgovski
%A Ashish A. Mahabal
%A Ciro Donalek
%A Victor Duan
%A Alison Maher
%J Physics
%D 2013
%I arXiv
%R 10.1093/mnras/stt1264
%X 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.
%U http://arxiv.org/abs/1307.2209v1