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Arxiv: Information content of JWST spectra of WASP-39b Published: 5/4/2024 3:51:50 PM Updated: 5/4/2024 3:51:50 PM

Paper abstract: WASP-39b was observed using several different JWST instrument modes and thespectra were published in a series of papers by the ERS team. The current studyexamines the information content of these spectra measured using the differentinstrument modes, focusing on the complexity of the temperature-pressureprofiles and number of chemical species warranted by the data. We examine ifH2O, CO, CO2, K, H2S, CH4, and SO2 are detected in each of the instrumentmodes. Two Bayesian inference methods are used to perform atmosphericretrievals: standard nested sampling and supervised machine learning of therandom forest (trained on a model grid). For nested sampling, Bayesian modelcomparison is used as a guide to identify the set of models with the requiredcomplexity to explain the data. Generally, non-isothermal transit chords areneeded to fit the transmission spectra of WASP-39b, although the complexity ofthe Tp-profile required is mode-dependent. The minimal set of chemical speciesneeded to fit a spectrum is mode-dependent as well, and also depends on whethergrey or non-grey clouds are assumed. When a non-grey cloud model is used to fitthe G395H spectrum, it generates a spectral continuum that compensates for theH2O opacity. The same compensation is absent when fitting the non-grey cloudmodel to the PRISM spectrum (which has broader wavelength coverage), suggestingthat it is spurious. The interplay between the cloud spectral continuum and theH2O opacity determines if SO2 is needed to fit either spectrum. The inferredelemental abundances of carbon and oxygen and the carbon-to-oxygen (C/O) ratiosare all mode- and model-dependent, and should be interpreted with caution.Bayesian model comparison does not always offer a clear path forward forfavouring specific retrieval models (e.g. grey versus non-grey clouds) and thusfor enabling unambiguous interpretations of exoplanet spectra.