Identification of carbon dioxide in an exoplanet atmosphere

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (that is, elements heavier than helium, also called ‘metallicity’)1–3, and thus the formation processes of the primary atmospheres of hot gas giants4–6. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets7–9. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2, but have not yielded definitive detections owing to the lack of unambiguous spectroscopic identification10–12. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science programme13,14. The data used in this study span 3.0–5.5 micrometres in wavelength and show a prominent CO2 absorption feature at 4.3 micrometres (26-sigma significance). The overall spectrum is well matched by one-dimensional, ten-times solar metallicity models that assume radiative–convective–thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 micrometres that is not reproduced by these models

Early Release Science of the exoplanet WASP-39b with JWST NIRSpec G395H

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData Availability: The data used in this paper are associated with JWST program ERS 1366 (observation #4) and are available from the Mikulski Archive for Space Telescopes (https://mast.stsci.edu). Science data processing version (SDP_VER) 2022_2a generated the uncalibrated data that we downloaded from MAST. We used JWST Calibration Pipeline software version (CAL_VER) 1.5.3 with modifications described in the text. We used calibration reference data from context (CRDS_CTX) 0916, except as noted in the text. All the data and models presented in this publication can be found at 10.5281/zenodo.7185300.Code Availability: The codes used in this publication to extract, reduce and analyze the data are as follows; STScI JWST Calibration pipeline45 (https://github.com/spacetelescope/jwst), Eureka!53 (https://eurekadocs.readthedocs.io/en/latest/), ExoTiC-JEDI47 (https://github.com/ExoTiC/ExoTiC-JEDI), juliet71 (https://juliet.readthedocs.io/en/latest/), Tiberius15,49,50, transitspectroscopy51 (https://github.com/nespinoza/transitspectroscopy). In addition, these made use of batman65 (http://lkreidberg.github.io/batman/docs/html/index.html), celerite86 (https://celerite.readthedocs.io/en/stable/), chromatic (https://zkbt.github.io/chromatic/), Dynesty72 (https://dynesty.readthedocs.io/en/stable/index.html), emcee69 (https://emcee.readthedocs.io/en/stable/), exoplanet83 (https://docs.exoplanet.codes/en/latest/), ExoTEP75–77, ExoTHETyS79 (https://github.com/ucl-exoplanets/ExoTETHyS), ExoTiCISM57 (https://github.com/Exo-TiC/ExoTiC-ISM), ExoTiC-LD58 (https://exoticld.readthedocs.io/en/latest/), george68 (https://george.readthedocs.io/en/latest/) JAX82 (https://jax.readthedocs.io/en/latest/), LMFIT70 (https://lmfit.github.io/lmfit-py/), Pylightcurve78 (https://github.com/ucl-exoplanets/pylightcurve), Pymc3138 (https://docs.pymc.io/en/v3/index.html) and Starry84 (https://starry.readthedocs.io/en/latest/), each of which use the standard python libraries astropy139,140, matplotlib141, numpy142, pandas143, scipy64 and xarray144. The atmospheric models used to fit the data can be found at ATMO[Tremblin2015,Drummond2016,Goyal2018,Goyal2020]88–91, PHOENIX92–94, PICASO98,99 (https://natashabatalha.github.io/picaso/), Virga98,107 (https://natashabatalha.github.io/virga/), and gCMCRT115 (https://github.com/ELeeAstro/gCMCRT).Measuring the abundances of carbon and oxygen in exoplanet atmospheres is considered a crucial avenue for unlocking the formation and evolution of exoplanetary systems. Access to an exoplanet’s chemical inventory requires high precision observations, often inferred from individual molecular detections with low-resolution space-based and high-resolution ground-based facilities. Here we report the medium-resolution (R≈600) transmission spectrum of an exoplanet atmosphere between 3–5 μm covering multiple absorption features for the Saturn-mass exoplanet WASP-39b, obtained with JWST NIRSpec G395H. Our observations achieve 1.46× photon precision, providing an average transit depth uncertainty of 221 ppm per spectroscopic bin, and present minimal impacts from systematic effects. We detect significant absorption from CO2 (28.5σ ) and H2O (21.5σ ), and identify SO2 as the source of absorption at 4.1 μ m (4.8σ ). Best-fit atmospheric models range between 3× and 10× solar metallicity, with sub-solar to solar C/O ratios. These results, including the detection of SO2, underscore the importance of characterising the chemistry in exoplanet atmospheres, and showcase NIRSpec G395H as an excellent mode for time series observations over this critical wavelength range.Science and Technology Facilities Council (STFC)UKR

A mini-chemical scheme with net reactions for 3D general circulation models. I. Thermochemical kinetics

Context. Growing evidence has indicated that the global composition distribution plays an indisputable role in interpreting observational data. Three-dimensional general circulation models (GCMs) with a reliable treatment of chemistry and clouds are particularly crucial in preparing for upcoming observations. In attempts to achieve 3D chemistry-climate modeling, the challenge mainly lies in the expensive computing power required for treating a large number of chemical species and reactions. Aims. Motivated by the need for a robust and computationally efficient chemical scheme, we devise a mini-chemical network with a minimal number of species and reactions for H2-dominated atmospheres. Methods. We apply a novel technique to simplify the chemical network from a full kinetics model, VULCAN, by replacing a large number of intermediate reactions with net reactions. The number of chemical species is cut down from 67 to 12, with the major species of thermal and observational importance retained, including H2O, CH4, CO, CO2, C2H2, NH3, and HCN. The size of the total reactions is also greatly reduced, from ~800 to 20. We validated the mini-chemical scheme by verifying the temporal evolution and benchmarking the predicted compositions in four exoplanet atmospheres (GJ 1214b, GJ 436b, HD 189733b, and HD 209458b) against the full kinetics of VULCAN. Results. The mini-network reproduces the chemical timescales and composition distributions of the full kinetics well within an order of magnitude for the major species in the pressure range of 1 bar–0.1 mbar across various metallicities and carbon-to-oxygen (C/O) ratios. Conclusions. We have developed and validated a mini-chemical scheme using net reactions to significantly simplify a large chemical network. The small scale of the mini-chemical scheme permits simple use and fast computation, which is optimal for implementation in a 3D GCM or a retrieval framework. We focus on the thermochemical kinetics of net reactions in this paper and address photochemistry in a follow-up paper

3D radiative-transfer for exoplanet atmospheres. gCMCRT: a GPU accelerated MCRT code

This is the final version. Available on open access from IOP Publishing via the DOI in this recordRadiative-transfer (RT) is a key component for investigating atmospheres of planetary bodies. With the 3D nature of exoplanet atmospheres being important in giving rise to their observable properties, accurate and fast 3D methods are required to be developed to meet future multi-dimensional and temporal data sets. We develop an open source GPU RT code, gCMCRT, a Monte Carlo RT forward model for general use in planetary atmosphere RT problems. We aim to automate the post-processing pipeline, starting from direct global circulation model (GCM) output to synthetic spectra. We develop albedo, emission and transmission spectra modes for 3D and 1D input structures. We include capability to use correlated-k and high-resolution opacity tables, the latter of which can be Doppler shifted inside the model. We post-process results from several GCM groups including ExoRad, SPARC/MITgcm THOR, UK Met Office UM, Exo-FMS and the Rauscher model. Users can therefore take advantage of desktop and HPC GPU computing solutions. gCMCRT is well suited for post-processing large GCM model grids produced by members of the community and for high-resolution 3D investigations.Swiss National Science Foundation (SNSF)Science and Technology Facilities Council (STFC)European Union Horizon 202

Chronotype and time-of-day effects on spatial working memory in preschool children

10.5664/jcsm.10650Journal of Clinical Sleep Medicine19101717-172