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

Astronomy and Astrophysics – Astrophysics

Scientific paper

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28 pages, 12 figures. Accepted and 'in press' for ApJ. Higher resolution versions for both this paper and astro-ph/0411233 are

Scientific paper

10.1086/427259

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.

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