Information content of JWST spectra of WASP-39b
arxiv(2024)
摘要
WASP-39b was observed using several different JWST instrument modes and the
spectra were published in a series of papers by the ERS team. 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
H2O, CO, CO2, K, H2S, CH4, and SO2 are detected in each of the instrument
modes. Two Bayesian inference methods are used to perform atmospheric
retrievals: standard nested sampling and supervised machine learning 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. Generally, non-isothermal transit chords are
needed to fit the transmission spectra of WASP-39b, although the complexity of
the Tp-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 G395H spectrum, it generates a spectral continuum that compensates for the
H2O opacity. The same compensation is absent when fitting the non-grey cloud
model to the PRISM spectrum (which has broader wavelength coverage), suggesting
that it is spurious. The interplay between the cloud spectral continuum and the
H2O opacity determines if SO2 is needed to fit either spectrum. 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.
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