Quick-MESS: A fast statistical tool for exoplanet imaging surveys

Several tools have been developed in the past few years for the statistical analysis of the exoplanet search surveys, mostly using a combination of Monte Carlo simulations or a Bayesian approach. Here we present Quick-MESS, a grid-based, non-Monte Carlo tool aimed to perform statistical analyses on results from direct imaging surveys, as well as help with the planning of these surveys. Quick-MESS uses the (expected) contrast curves for direct imaging surveys to assess for each target the probability that a planet of a given mass and semimajor axis can be detected. By using a grid-based approach, Quick-MESS is typically more than an order of magnitude faster than tools based on Monte Carlo sampling of the planet distribution. In addition, Quick-MESS is extremely flexible, enabling the study of a large range of parameter space for the mass and semimajor axes distributions without the need of resimulating the planet distribution. In order to show examples of the capabilities of Quick-MESS, we present the analysis of the Gemini Deep Planet Survey and the predictions for upcoming surveys with extreme-AO instruments.