Fast identification of transits from light-curves

We present an algorithm that allows fast and efficient detection of transits, including planetary transits, from light-curves. The method is based on building an ensemble of fiducial models and compressing the data using the moped compression algorithm. We describe the method and demonstrate its efficiency by finding planet-like transits in simulated Panoramic Survey Telescope & Rapid Response System (Pan-STARRS) light-curves. We show that our method is independent of the size of the search space of transit parameters. In large sets of light-curves, we achieve speed-up factors of the order of 10³ times over an optimized adaptive search in the χ² space. We discuss how the algorithm can be used in forthcoming large surveys like Pan-STARRS and the Large Synoptic Survey Telescope (LSST), and how it may be optimized for future space missions like Kepler and COROT where most of the processing must be done on board.