Journal
MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY
Volume 434, Issue 4, Pages 3423-3444Publisher
OXFORD UNIV PRESS
DOI: 10.1093/mnras/stt1264
Keywords
methods: data analysis; techniques: photometric; astronomical data bases: miscellaneous; virtual observatory tools
Categories
Funding
- NSF [AST-0909182, IIS-1118041, AST-0834235]
- W. M. Keck Institute for Space Studies
- US Virtual Astronomical Observatory
- National Science Foundation
- National Aeronautics and Space Administration
- Direct For Mathematical & Physical Scien
- Division Of Astronomical Sciences [1313422] Funding Source: National Science Foundation
- Div Of Information & Intelligent Systems
- Direct For Computer & Info Scie & Enginr [1118041] Funding Source: National Science Foundation
Ask authors/readers for more resources
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, MACHO and ASAS data sets. We analyse 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 dependences 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.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available