A retrieval challenge exercise for the Ariel mission

TL;DR

This paper presents a retrieval challenge for the Ariel mission, demonstrating that different atmospheric retrieval codes can reliably recover exoplanet parameters from synthetic data, ensuring data analysis consistency for the upcoming mission.

Contribution

It introduces a comparative retrieval challenge using multiple codes on synthetic datasets, highlighting their ability to produce consistent and accurate exoplanet atmospheric parameters.

Findings

High agreement among retrieval codes

Most codes recover correct input solutions

Retrieval reproducibility is confirmed

Abstract

The Ariel mission, due to launch in 2029, will obtain spectroscopic information for 1000 exoplanets, providing an unprecedented opportunity for comparative exoplanetology. Retrieval codes - parameteric atmospheric models coupled with an inversion algorithm - represent the tool of choice for interpreting Ariel data. Ensuring that reliable and consistent results can be produced by these tools is a critical preparatory step for the mission. Here, we present the results of a retrieval challenge. We use five different exoplanet retrieval codes to analyse the same synthetic datasets, and test a) the ability of each to recover the correct input solution and b) the consistency of the results. We find that generally there is very good agreement between the five codes, and in the majority of cases the correct solutions are recovered. This demonstrates the reproducibility of retrievals for transit spectra of exoplanets, even when codes are not previously benchmarked against each other.