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MESS is a Monte Carlo simulation IDL code which uses either the results of the statistical analysis of the properties of discovered planets, or the results of the planet formation theories, to build synthetic planet populations fully described in terms of frequency, orbital elements and physical properties. They can then be used to either test the consistency of their properties with the observed population of planets given different detection techniques or to actually predict the expected number of planets for future surveys. It can be used to probe the physical and orbital properties of a putative companion within the circumstellar disk of a given star and to test constrain the orbital distribution properties of a potential planet population around the members of the TW Hydrae association. Finally, using in its predictive mode, the synergy of future space and ground-based telescopes instrumentation has been investigated to identify the mass-period parameter space that will be probed in future surveys for giant and rocky planets. A Python version of this code, Exo-DMC (ascl:2010.008), is available.
The Exoplanet Detection Map Calculator (Exo-DMC) performs statistical analysis of exoplanet surveys results using Monte Carlo methods. Written in Python, it is the latest rendition of the MESS (Multi-purpose Exoplanet Simulation System, ascl:1111.009). Exo-DMC combines the information on the target stars with instrument detection limits to estimate the probability of detection of companions within a user defined range of masses and physical separations, ultimately generating detection probability maps. The software allows for a high level of flexibility in terms of possible assumptions on the synthetic planet population to be used for the determination of the detection probability.
MADYS (Manifold Age Determination for Young Stars) determines the age and mass of young stellar and substellar objects. The code automatically retrieves and cross-matches photometry from several catalogs, estimates interstellar extinction, and derives age and mass estimates for individual objects through isochronal fitting. MADYS harmonizes the heterogeneity of publicly-available isochrone grids and the user can choose amongst several models, some of which have customizable astrophysical parameters. Particular attention has been dedicated to the categorization of these models, labeled through a four-level taxonomical classification.