Abstract

Studying chemical composition is fundamental to modeling the formation history of planets and planetary systems. With the first JWST data and the upcoming Ariel satellite, we expect a leap forward in the exoplanet’s atmosphere field. That’s why we propose here an analysis of five targets to improve the determination of their composition and the chemical mechanisms that take place in their atmospheres, combining multiple instruments and using retrieval methods. Our five targets are HAT-P-12b, HD 209458b, WASP-6b, WASP-17b, and WASP-39b, which have temperatures ranging from 1000K to 1700K and radii ranging from 0.9 to 1.9 Jupiter radius. We use spatially scanned observations from the grisms G102 and G141 of the Wide Field Camera 3 (WFC3) on the Hubble Space Telescope, with a wavelength coverage of 0.8 to 1.7 microns. We analyze these data with the publicly available Iraclis pipeline (Tsiaras et al. (2018)). We added to our datasets Space Telescope Imaging Spectrograph (STIS) observations, reduced and presented in Sing et al. (2015), to increase our wavelength coverage from 0.4 to 1.7 microns. We then perform a Bayesian retrieval analysis with the open-source TauREx (Al-Refaie et al. (2019)) using a nested sampling algorithm. We perform the retrieval considering molecular abundances varying freely and with equilibrium chemistry ACE (Agúndez et al. (2012, 2020)) and FastChem (Stock et al. (2018)). The principle is to start from a transmission spectroscopy dataset and to seek the model that characterizes the atmosphere in the most probable way, in other words, the spectrum that best fits the data points. This work is detailed in a dedicated paper published in the Astronomy \& Astrophysics journal (Panek et al. (2023)). For very hot planets, thermochemical equilibrium may be close to reality, but for less hot planets, vertical mixing and photodissociation bring these planets out of equilibrium. That's why our results will soon be extended to a non-equilibrium thermochemistry model (Venot et al. (2020)).

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