Quick-MESS: A fast statistical tool for Exoplanet Imaging Surveys

TL;DR

Quick-MESS is a fast, grid-based statistical tool designed for analyzing and planning exoplanet imaging surveys, offering significant speed improvements over traditional Monte Carlo methods.

Contribution

It introduces a novel, efficient grid-based approach for exoplanet survey analysis that is faster and more flexible than existing Monte Carlo-based tools.

Findings

Over an order of magnitude faster than Monte Carlo methods

Flexible in exploring parameter space without re-simulation

Successfully applied to Gemini Deep Planet Survey and future predictions

Abstract

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 the Quick-MESS, a grid-based, non-Monte Carlo tool aimed to perform statistical analyses on results from and help with the planning of direct imaging 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 semi-major 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 semi-major axes distributions without the need of re-simulating the planet distribution. In order to show examples of the capabilities of the Quick-MESS, we present the analysis of the Gemini Deep Planet Survey and the predictions for upcoming surveys with extreme-AO instruments.