ExoLyn: a golden mean approach to multi-species cloud modelling in atmospheric retrieval

Abstract

Context. Clouds are ubiquitous in exoplanets' atmospheres and play an important role in setting the opacity and chemical inventory of the atmosphere. Understanding clouds is a critical step in interpreting exoplanets' spectroscopic data. Aims. The aim is to model the multi-species nature of clouds in atmospheric retrieval studies. To this end, we develop ExoLyn - a 1D cloud model that balances physical consistency with computational efficiency. Methods. ExoLyn solves the transport equation of cloud particles and vapor under cloud condensation rates that are self-consistently calculated from thermodynamics. ExoLyn is a standalone, open source package capable to be combined with \texttt{optool} to calculate solid opacities and with \texttt{petitRADTRANS} to generate transmission or emission spectra. Results. With ExoLyn we find that the compositional structure of clouds in hot Jupiter planets' atmospheres is layered with a cloud dominated by magnesium-silicates on top of an iron cloud. This finding is consistent with more complex cloud formation models but can be obtained with ExoLyn in only a few seconds. The composition of the cloud particles can be constrained from the spectrum, for example, MgSiO3 and Mg2SiO4 components give rise to an absorption feature at 8 - 10 um. We investigate the dependence of the cloud structure on the bulk elemental composition of the planet and find that SiO2-dominated clouds forms on metal-rich planet and Fe clouds with strong extinction effect forms on C-rich planet. Conclusions. Designed towards maximum flexibility, ExoLyn can also be used in retrieval analysis of sub-Neptunes and self-luminous planets. The efficiency of ExoLyn opens the possibility of joint retrieval of exoplanets' gas and cloud components.