MCMCI: A code to fully characterise an exoplanetary system

Abstract

Context. Useful information can be retrieved by analysing the transit light curve of a planet-hosting star or induced radial velocity oscillations. However, inferring the physical parameters of the planet, such as mass, size, and semi-major axis, requires preliminary knowledge of some parameters of the host star, especially its mass or radius, which are generally inferred through theoretical evolutionary models. Aims. We seek to present and test a whole algorithm devoted to the complete characterisation of an exoplanetary system thanks to the global analysis of photometric or radial velocity time series combined with observational stellar parameters derived either from spectroscopy or photometry. Methods. We developed an integrated tool called MCMCI. This tool combines the Markov chain Monte Carlo (MCMC) approach of analysing photometric or radial velocity time series with a proper interpolation within stellar evolutionary isochrones and tracks, known as isochrone placement, to be performed at each chain step, to retrieve stellar theoretical parameters such as age, mass, and radius.Results. We tested the MCMCI on the HD 219134 multi-planetary system hosting two transiting rocky super Earths and on WASP-4, which hosts a bloated hot Jupiter. Even considering different input approaches, a final convergence was reached within the code, we found good agreement with the results already stated in the literature and we obtained more precise output parameters, especially concerning planetary masses. Conclusions. The MCMCI tool offers the opportunity to perform an integrated analysis of an exoplanetary system without splitting it into the preliminary stellar characterisation through theoretical models. Rather this approach favours a close interaction between light curve analysis and isochrones, so that the parameters recovered at each step of the MCMC enter as inputs for purposes of isochrone placement.A&A proofs: manuscript no. mcmcIsoc sits are expected to be available as a result of already active and forthcoming missions.Our unified approach of simultaneously modelling the star and its planets is remarkable even if it is not unique, since it has already been followed, for example by Hartman et al. (2019), who carry out an isochrone-based joint analysis using a differential evolution MCMC procedure (Ter Braak 2006) and PARSEC stellar evolutionary models (Marigo et al. 2017). Also Siverd et al. (2012) simultaneously model the stellar host and its companion, but to break the M -R degeneracy they simply consider the mass-radius relation by Torres et al. (2010), as they use the first version of the Idl fitting package EXOFAST (Eastman et al. 2013). We notice that our version of MCMC without the support of stellar evolutionary models also allows us to select a modified version of the Torres et al. (2010) M -R law from wellconstrained detached binary systems (Gillon et al. 2011); thus we can use this tool during the LC or RV fitting. Recently, a new version of the EXOFAST package called EXOFASTv2 has been released (Eastman et...

pyaneti – II. A multidimensional Gaussian process approach to analysing spectroscopic time-series

“…Fortunately, the wealth of exoplanetary data has spurred the development of a variety of exoplanet numerical tools. To our knowledge, the codes that allow one to analyse jointly RV and transit data are: allesfitter (Günther & Daylan 2020), EXOFAST (Eastman et al 2013(Eastman et al , 2019, exoplanet (Foreman-Mackey et al 2021), Exo-Stricker (Trifonov 2019), juliet (Espinoza et al 2019), MCMCI (Bonfanti & Gillon 2020), PASTIS (Díaz et al 2014;Santerne et al 2015), PlanetPAck (Baluev 2013), TLCM (Csizmadia 2020), and pyaneti (Barragán et al 2019a). These software packages cover a wide range of programming languages and models, and have been used extensively in the literature.…”

More planetary candidates from K2 Campaign 5 using TRAN_K2

“…The most prominent downward outlier was WASP-4 (Wilson et al 2008). All current stellar radius values are in the close neighborhood of 0.90 R/R (Bonfanti & Gillon 2020), making it difficult to increase the calculated Q tran value. High-resolution imaging (Bergfors et al 2013) does not indicate any nearby companion that might indirectly affect the transit duration.…”

Discovery of a young low-mass brown dwarf transiting a fast-rotating F-type star by the Galactic Plane eXoplanet (GPX) survey

“…MCMCI is a code that utilises Markov Chain Monte Carlo (MCMC) stochastic simulations of the RV and photometric data to analyse the posterior probability distribution function (PDF) of the model parameters coupled with the isochrone placement algorithm. The MCMCI code and the logic behind it are described in details in Bonfanti & Gillon (2020) and here we outline the main aspects of our analysis. The MCMCI tool performs an integrated three-step analysis:…”