A Method for the Detection of Planetary Transits in Large Time-Series Datasets

Abstract

We present a fast, efficient and easy to apply computational method for the detection of planetary transits in large photometric datasets. The code has been specifically produced to analyse an ensemble of 21,950 stars in the globular cluster 47 Tucanae, the results of which are the subject of a separate paper. Using cross correlation techniques and Monte Carlo tested detection criteria, each time-series is compared with a large database of appropriate transit models. The algorithm recovers transit signatures with high efficiency while maintaining a low false detection probability, even in noisy data. This is illustrated by describing its application to our 47 Tuc dataset, for which the algorithm produced a weighted mean transit recoverabilty spanning 85% to 25% for orbital periods of 1-16 days despite gaps in the time series caused by weather and observing duty cycle. The code is easily adaptable and is currently designed to accept time-series produced using Difference Imaging Analysis.

28 pages, 12 figures. Accepted and 'in press' for ApJ. Higher resolution versions for both this paper and astro-ph/0411233 are available at http://www.mso.anu.edu.au/~dtfw

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Cited by in corpus (8)

• Terrestrial Planet Occurrence Rates for the Kepler GK Dwarf Sample
• An Absence of Hot Jupiter Planets in 47 Tucanae: Results of a Wide-Field Transit Search
• The Quasiperiodic Automated Transit Search Algorithm
• Searching for Transiting Planets in Stellar Systems
• The Frequency of Large Radius Hot and Very Hot Jupiters in omega Centauri
• Lupus-TR-3b: A Low-Mass Transiting Hot Jupiter in the Galactic Plane?
• Efficient analysis in planet transit surveys
• Bright low mass eclipsing binary candidates observed by STEREO