Kavli Affiliate: Bruce Macintosh
| First 5 Authors: Simon Petrus, Niall Whiteford, Polychronis Patapis, Beth A. Biller, Andrew Skemer
| Summary:
The unprecedented medium-resolution (R~1500-3500) near- and mid-infrared
(1-18um) spectrum provided by JWST for the young (140+/-20Myr) low-mass
(12-20MJup) L-T transition (L7) companion VHS1256b gives access to a catalogue
of molecular absorptions. In this study, we present a comprehensive analysis of
this dataset utilizing a forward modelling approach, applying our Bayesian
framework, ForMoSA. We explore five distinct atmospheric models to assess their
performance in estimating key atmospheric parameters: Teff, log(g), [M/H], C/O,
gamma, fsed, and R. Our findings reveal that each parameter’s estimate is
significantly influenced by factors such as the wavelength range considered and
the model chosen for the fit. This is attributed to systematic errors in the
models and their challenges in accurately replicating the complex atmospheric
structure of VHS1256b, notably the complexity of its clouds and dust
distribution. To propagate the impact of these systematic uncertainties on our
atmospheric property estimates, we introduce innovative fitting methodologies
based on independent fits performed on different spectral windows. We finally
derived a Teff consistent with the spectral type of the target, considering its
young age, which is confirmed by our estimate of log(g). Despite the
exceptional data quality, attaining robust estimates for chemical abundances
[M/H] and C/O, often employed as indicators of formation history, remains
challenging. Nevertheless, the pioneering case of JWST’s data for VHS1256b has
paved the way for future acquisitions of substellar spectra that will be
systematically analyzed to directly compare the properties of these objects and
correct the systematics in the models.
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