In this work, we present Alfnoor, a dedicated tool optimised 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 randomised the abundances - ranging from 10$^{-7}$ to 10$^{-2}$ - of the trace gases, which include H$_2$O, CH$_4$, CO, CO$_2$ and NH$_3$. This exercise allowed 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.

中文翻译：

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Alfnoor：Ariel 目标列表的检索模拟

在这项工作中，我们展示了 Alfnoor，这是一种针对系外行星大气人口研究进行了优化的专用工具。Alfnoor 将最新版本的反演算法 TauREx 3 与仪器噪声模拟器 ArielRad 相结合，可以同时对大量外大气样本进行反演分析。我们将此工具应用于 Ariel 候选行星列表，并专注于使用 Tier-2 模式（中等 Ariel 分辨率）在传输过程中观察到的以氢为主的多云大气。作为第一个实验，我们随机分配了痕量气体的丰度 - 从 10$^{-7}$ 到 10$^{-2}$ - 包括 H$_2$O、CH$_4$、CO、 CO$_2$ 和 NH$_3$。此练习允许估计存在云时 Ariel Tier-2 和 Tier-3 模式的检测限。在第二个实验中，我们在化学物种和地球的有效温度之间强加了任意趋势。运行最后一个实验，要求分子丰度由特定温度下的平衡化学决定。我们的结果证明了 Ariel Tier-2 和 Tier-3 调查能够揭示化学和相关行星参数之间的趋势。未来的工作将集中在日食数据、比氢重的大气层上，并将应用于其他天文台。