Detecting transiting exoplanets in simulated PLATO data. A comparison of light curve filter and transit search algorithms

Abstract

Our goal is to test and compare transit search methodologies, and provide recommendations as to the best practices to be implemented by the upcoming ESA PLATO mission, in order to achieve its goal of detecting Earth-like planets in the habitable zones of Sun-like stars. We generated simulated two-year PLATO light curves with injected planets with sizes 0.5--2.0 R_⊕, and compared the performance of the ̧etra , ̆mbra , and νance transit search methods. ̧etra and ̆mbra require pre-filtered light curves and we tested four filters: the biweight, Huber spline, LOcally WEighted Scatterplot Smoothing (LOWESS), and the LOWESS-based young stars detrending (YSD) filters. νance uses a Gaussian process to model the stellar variability at all proposed transit parameters. νance achieves the best performance, recovering 61.2% of signals using a simple harmonic oscillator Gaussian process kernel, and it performs especially well for both hot and fast-rotating stars. However, when multiple Huber spline filter windows are considered, both ̧etra and ̆mbra can match νance 's performance. Using four windows ̧etra recovers 61.3% of signals, and using just two windows ̆mbra recovers 61.7% of signals. Recovery rates exceeding νance are possible by using more windows. The computational cost of running νance is so high that running ̧etra or ̆mbra on multiple windows is preferred. The PLATO pipeline should use the Huber spline with a range of window sizes as its primary light curve filter. ̧etra should be updated to use the warped least-squares templates implemented in ̆mbra . The use of νance should be considered for hot, rapidly rotating stars.