A quench-pressure parameterisation with two free parameters recovers unbiased C/O and [M/H] from synthetic JWST spectra with vertical mixing, and tentatively detects quenching and photochemical H2S depletion in HD 189733b NIRCam data.
NEMESISPY: A Python package for simulating and retrieving exoplanetary spectra
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abstract
NEMESISPY is a Python package developed to perform parametric atmospheric modelling and radiative transfer calculation for the retrievals of exoplanetary spectra. It is a recent development of the well-established Fortran NEMESIS library (P. G. J. Irwin et al., 2008), which has been applied to the atmospheric retrievals of both solar system planets and exoplanets employing numerous different observing geometries. NEMESISPY can be easily interfaced with Bayesian inference algorithms to retrieve atmospheric properties from spectroscopic observations. Recently, NEMESISPY has been applied to the retrievals of Hubble and Spitzer data of a hot Jupiter (Yang et al., 2023), as well as to JWST/Mid-Infrared Instrument (JWST/MIRI) data of a hot Jupiter (Yang et al., 2024).
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A parameterised approach to disequilibrium retrievals in the JWST era: Application to NIRCam observations of HD 189733b
A quench-pressure parameterisation with two free parameters recovers unbiased C/O and [M/H] from synthetic JWST spectra with vertical mixing, and tentatively detects quenching and photochemical H2S depletion in HD 189733b NIRCam data.