Transit algorithm performance using real WASP data

Context. Many transiting exoplanet surveys are now in operation, observing millions of stars and searching for the periodic signals that may indicate planets orbiting these objects. Aims: We have tested the performance of transit detection algorithms using real WASP data, avoiding the issue of generating the appropriate level of white and red noise in simulated lightcurves. We used a two-dimensional search method, the box-least-squares (BLS) algorithm, and two- and three-dimensional versions of the analysis of variance (AoV) method. Methods: After removing any potential transiting candidate or variable objects, transits were injected into each lightcurve. We performed Monte Carlo simulations, testing the recovery of injected signals in 99 lightcurves by each algorithm. Results: In the simulations using data from one season of WASP observations, it was determined that the BLS method should detect a total of 37% of planets and the 3D AoV 23%. Simulations to explore the effects of extending survey baseline or number of hours of observations per 24 h period, i.e. longitudinally spaced observatories, were also performed. They showed that increasing the coverage via an increase in baseline or in observational hours are equally good for maximising overall detections of transiting planets. The resulting algorithm performance was combined with actual WASP-South results to estimate that 0.08% and 0.30% of stars harbour very hot Jupiters and hot Jupiters respectively.