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 algorithm. We describe the method and demonstrate its efficiency by finding planet-like transits in simulated Pan-STARRS light-curves. We show that 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 order of $10^{8}$ times over the full $\chi2$ search. We discuss how the algorithm can be used in forthcoming large surveys like Pan-STARRS and 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.