Information content of JWST spectra of WASP-39b

¹ Ludwig Maximilian University, Faculty of Physics, University Observatory, Scheinerstr. 1, Munich 81679, Germany
e-mail: anna.lueber@physik.lmu.de
² Valongo Observatory, Federal University of Rio de Janeiro, Ladeira do Pedro Antonio, 43, 20080-090, Rio de Janeiro, Brazil
e-mail: aline12@ov.ufrj.br
³ Astrophysics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH, UK
⁴ ARTORG Center for Biomedical Engineering Research, University of Bern, Murtenstrasse 50, 3008 Bern, Switzerland
⁵ University College London, Department of Physics & Astronomy, Gower St, London, WC1E 6BT, UK
⁶ University of Warwick, Department of Physics, Astronomy & Astrophysics Group, Coventry CV4 7AL, UK
⁷ Center for Space and Habitability, University of Bern, Gesellschaftsstrasse 6, CH-3012, Bern, Switzerland

Received: 30 November 2023
Accepted: 2 May 2024

Abstract

Context. The era of James Webb Space Telescope (JWST) transmission spectroscopy of exoplanetary atmospheres commenced with the study of the Saturn-mass gas giant WASP-39b as part of the Early Release Science (ERS) program. WASP-39b was observed using several different JWST instrument modes (NIRCam,, NIRISS, NIRSpec G395H and NIRSpec PRISM) and the spectra were published in a series of papers by the ERS team.

Aims. The current study examines the information content of these spectra measured using the different instrument modes, focusing on the complexity of the temperature-pressure profiles and number of chemical species warranted by the data. We examine if the molecules H₂O, CO, CO₂, K, H₂S, CH₄, and SO₂ are detected in each of the instrument modes.

Methods. Two Bayesian inference methods are used to perform atmospheric retrievals: the standard nested sampling method, as well as the supervised machine learning method of the random forest (trained on a model grid). For nested sampling, Bayesian model comparison is used as a guide to identify the set of models with the required complexity to explain the data.

Results. Generally, non-isothermal transit chords are needed to fit the transmission spectra of WASP-39b, although the complexity of the temperature-pressure profile required is mode-dependent. The minimal set of chemical species needed to fit a spectrum is mode-dependent as well, and also depends on whether grey or non-grey clouds are assumed. When a non-grey cloud model is used to fit the NIRSpec G395H spectrum, it generates a spectral continuum that compensates for the water opacity. The same compensation is absent when fitting the non-grey cloud model to the NIRSpec PRISM spectrum (which has broader wavelength coverage), suggesting that it is spurious. The interplay between the cloud spectral continuum and the water opacity determines if sulphur dioxide is needed to fit either spectrum.

Conclusions. The inferred elemental abundances of carbon and oxygen and the carbon-to-oxygen (C/O) ratios are all mode- and model-dependent, and should be interpreted with caution. Bayesian model comparison does not always offer a clear path forward for favouring specific retrieval models (e.g. grey versus non-grey clouds) and thus for enabling unambiguous interpretations of exoplanet spectra.