Alfnoor: assessing the information content of Ariel's low resolution spectra with planetary population studies

TL;DR

This paper evaluates the information content of ARIEL's low resolution exoplanet spectra, proposing methods for candidate selection, atmospheric classification, and data exploitation to enhance planetary population studies.

Contribution

It introduces a strategy for selecting planets for higher resolution follow-up, a metric for preliminary atmospheric classification, and explores new methods to maximize data scientific content.

Findings

Proposed a candidate selection strategy for reobservation.

Developed a metric for atmospheric classification without retrieval.

Explored alternative methods to analyze spectral data.

Abstract

The ARIEL Space Telescope will provide a large and diverse sample of exoplanet spectra, performing spectroscopic observations of about 1000 exoplanets in the wavelength range $0.5 \to 7.8 \; \mu m$. In this paper, we investigate the information content of ARIEL's Reconnaissance Survey low resolution transmission spectra. Among the goals of the ARIEL Reconnaissance Survey is also to identify planets without molecular features in their atmosphere. In this work, (1) we present a strategy that will allow to select candidate planets to be reobserved in a ARIEL's higher resolution Tier; (2) we propose a metric to preliminary classify exoplanets by their atmospheric composition without performing an atmospheric retrieval; (3) we introduce the possibility to find other methods to better exploit the data scientific content.