The 2020 release of the ExoMol database: molecular line lists for exoplanet and other hot atmospheres

Abstract

The ExoMol database (www.exomol.com) provides molecular data for spectroscopic studies of hot atmospheres. While the data is intended for studies of exoplanets and other astronomical bodies, the dataset is widely applicable. The basic form of the database is extensive line lists; these are supplemented with partition functions, state lifetimes, cooling functions, Landé gfactors, temperature-dependent cross sections, opacities, pressure broadening parameters, k-coefficients and dipoles. This paper presents the latest release of the database which has been expanded to consider 80 molecules and 190 isotopologues totaling over 700 billion transitions. While the spectroscopic data is 1

A solar C/O and sub-solar metallicity in a hot Jupiter atmosphere

“…Rather than apply the standard cross-correlation analysis, we opt to use a Bayesian analysis/loglikelihood and modeling framework 14 so as to directly determine the atmospheric temperature/ abundance constraints. We update our radiative transfer model 14,35,36 to include the latest line lists from EXOMOL 37 and HITEMP 38 -CH4:HITEMP 39 , CO:HITEMP 40 , NH3:aCeTY super-lines, H2S:AYT2 41 , HCN: Harris 42 , along with H 2 -H 2 /He collision induced absorption: HITRAN 43 . We include separately the 12 C 16 O and 13 C 16 O lines weighted by the built in terrestrial ratio of 1:89 ( 13 C: 12 C) in the HITRAN/HITEMP line lists.…”

KELT-11 b: Abundances of water and constraints on carbon-bearing molecules from the Hubble transmission spectrum

“…The observed spectrum (Appendix 2) was analysed using our Bayesian retrieval framework TauREx 3 (Waldmann et al 2015b,a;Al-Refaie et al 2019;Al-Refaie et al 2020), which was recently benchmarked (Barstow et al 2020) against the other retrieval codes NEMESIS (Irwin et al 2008) and CHIMERA (Line et al 2013). We utilised the absorption cross-sections from the Exo-Mol database (Tennyson & Yurchenko 2012;Tennyson et al 2016Tennyson et al , 2020Chubb et al 2020) and explored the parameter space with the algorithm MultiNest (Feroz et al 2009) with 750 live points and an evidence tolerance of 0.5. We adopted uniform priors for all the free parameters.…”