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

M. Bonavita, E. J.W. De Mooij, R. Jayawardhana

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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 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.

Original languageEnglish
Pages (from-to)849-856
Number of pages8
JournalPublications of the Astronomical Society of the Pacific
Volume125
Issue number929
DOIs
Publication statusPublished - 01 Jul 2013
Externally publishedYes

ASJC Scopus subject areas

  • Astronomy and Astrophysics
  • Space and Planetary Science

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