Published September 2013
| Submitted + Published
Journal Article
Open
Using conditional entropy to identify periodicity
Abstract
This paper presents a new period-finding method based on conditional entropy that is both efficient and accurate. We demonstrate its applicability on simulated and real data. We find that it has comparable performance to other information-based techniques with simulated data but is superior with real data, both for finding periods and for just identifying periodic behaviour. In particular, it is robust against common aliasing issues found with other period-finding algorithms.
Additional Information
© 2013 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. Accepted 2013 June 27. Received 2013 June 26; in original form 2013 June 4. First published online: July 26, 2013. We thank the referee, Pablo Cincotta, for his useful comments. This work was supported in part by the NSF grants AST-0909182 and IIS-1118041, by the W. M. Keck Institute for Space Studies, and by the US Virtual Astronomical Observatory, itself supported by the NSF grant AST-0834235.Attached Files
Published - MNRAS-2013-Graham-2629-35.pdf
Submitted - 1306.6664v2.pdf
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MNRAS-2013-Graham-2629-35.pdf
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Additional details
- Eprint ID
- 41615
- Resolver ID
- CaltechAUTHORS:20131002-125112999
- AST-0909182
- NSF
- IIS-1118041
- NSF
- W. M. Keck Institute for Space Studies
- US Virtual Astronomical Observatory
- AST-0834235
- NSF
- Created
-
2013-10-02Created from EPrint's datestamp field
- Updated
-
2021-11-10Created from EPrint's last_modified field
- Caltech groups
- Keck Institute for Space Studies