Bocchieri, Andrea;
Mugnai, Lorenzo V;
Pascale, Enzo;
Changeat, Quentin;
Tinetti, Giovanna;
(2023)
Detecting molecules in Ariel low resolution transmission spectra.
Experimental Astronomy
10.1007/s10686-023-09911-x.
(In press).
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Abstract
The Ariel Space Mission aims to observe a diverse sample of exoplanet atmospheres across a wide wavelength range of 0.5 to 7.8 microns. The observations are organized into four Tiers, with Tier 1 being a reconnaissance survey. This Tier is designed to achieve a sufficient signal-to-noise ratio (S/N) at low spectral resolution in order to identify featureless spectra or detect key molecular species without necessarily constraining their abundances with high confidence. We introduce a P-statistic that uses the abundance posteriors from a spectral retrieval to infer the probability of a molecule’s presence in a given planet’s atmosphere in Tier 1. We find that this method predicts probabilities that correlate well with the input abundances, indicating considerable predictive power when retrieval models have comparable or higher complexity compared to the data. However, we also demonstrate that the P-statistic loses representativity when the retrieval model has lower complexity, expressed as the inclusion of fewer than the expected molecules. The reliability and predictive power of the P-statistic are assessed on a simulated population of exoplanets with H2-He dominated atmospheres, and forecasting biases are studied and found not to adversely affect the classification of the survey.
| Type: | Article |
|---|---|
| Title: | Detecting molecules in Ariel low resolution transmission spectra |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s10686-023-09911-x |
| Publisher version: | https://doi.org/10.1007/s10686-023-09911-x |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Methods: data analysis, Planets, and satellites: atmospheres, Surveys, Techniques: spectroscopic |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10177378 |
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