paper

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

arXiv:2409.18181 · doi:10.1051/0004-6361/202451112

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.

17 pages, 12 figures, accepted by A&A

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