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In this work, we present Alfnoor, a dedicated tool optimized for population studies of exoplanet atmospheres. Alfnoor combines the latest version of the retrieval algorithm, TauREx 3, with the instrument noise simulator ArielRad and enables the simultaneous retrieval analysis of a large sample of exo-atmospheres. We applied this tool to the Ariel list of planetary candidates and focus on hydrogen dominated, cloudy atmospheres observed in transit with the Tier-2 mode (medium Ariel resolution). As a first experiment, we randomized the abundances—ranging from 10^−7 to 10^−2—of the trace gases, which include H2O, CH4, CO, CO2, and NH3. This exercise allowed us to estimate the detection limits for Ariel Tier-2 and Tier-3 modes when clouds are present. In a second experiment, we imposed an arbitrary trend between a chemical species and the effective temperature of the planet. A last experiment was run requiring molecular abundances being dictated by equilibrium chemistry at a certain temperature. Our results demonstrate the ability of Ariel Tier-2 and Tier-3 surveys to reveal trends between the chemistry and associated planetary parameters. Future work will focus on eclipse data, on atmospheres heavier than hydrogen, and will be applied also to other observatories.

Alfnoor: A Retrieval Simulation of the Ariel Target List / Changeat, Quentin.; Al-Refaie, Ahmed.; Mugnai, Lorenzo V.; Edwards, Billy; Waldmann, Ingo. P.; Pascale, Enzo.; Tinetti, Giovanna.. - In: THE ASTRONOMICAL JOURNAL. - ISSN 0004-6256. - 160:2(2020), p. 80. [10.3847/1538-3881/ab9a53]

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