The BAST algorithm for transit detection

Abstract

The pioneer space mission for photometric exoplanet searches, CoRoT, steadily monitors about 12000 stars in each of its fields of view. Transit detection algorithms are applied to derive promising planetary candidates, which are then followed-up with ground-based observations. We present BAST (Berlin Automatic Search for Transits), a new algorithm for periodic transit detection, and test it on simulated CoRoT data. BAST searches for box-shaped signals in normalized, filtered, variability-fitted, and unfolded light curves. A low-pass filter is applied to remove high-frequency signals, and linear fits to subsections of data are subtracted to remove the star's variability. A search for periodicity is then performed in transit events identified above a given detection threshold. Some criteria are defined to better separate planet candidates from binary stars. From the analysis of simulated CoRoT light curves, we show that the BAST detection performance is similar to that of the Box-fitting Least-Square (BLS) method if the signal-to-noise ratio is high. However, the BAST box search for transits computes 10 times faster than the BLS method. By adding periodic transits to simulated CoRoT data, we show that the minimum periodic depth detectable with BAST is a linearly increasing function of the noise level. For low-noise light curves, the detection limit corresponds to a transit depth d~0.01%, i.e. a planet of 1 Earth radius around a solar-type star.

4 pages, 3 figures, to be published in A&A

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Cited by in corpus (13)

• Transit Least Squares: Optimized transit detection algorithm to search for periodic transits of small planets
• The rotation of field stars from CoRoT data
• The Quasiperiodic Automated Transit Search Algorithm
• A study of the performance of the transit detection tool DST in space-based surveys. Application of the CoRoT pipeline to Kepler data
• Overview of semi-sinusoidal stellar variability with the CoRoT satellite
• Planetary transit candidates in the CoRoT LRa01 field
• Transit least-squares survey -- II. Discovery and validation of 17 new sub- to super-Earth-sized planets in multi-planet systems from K2
• New Insights into Time Series Analysis - I - Correlated observations
• The variability behavior of CoRoT M-giant Stars
• Detecting Variability in Massive Astronomical Time-Series Data II: Variable Candidates in the Northern Sky Variability Survey
• Sparse Box-fitting Least Squares
• The GPU Phase Folding and Deep Learning Method for Detecting Exoplanet Transits
• Planetary transit candidates in COROT-IRa01 field