MELTYQ couples magma-atmosphere equilibrium models with spectral retrievals to constrain sub-Neptune magma oxidation states and volatile inventories from transmission spectra.
pp EPSC2022--1114 ( @eprint arXiv 2104.04824 ), @doi 10.5194/epsc2022-1114
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Coupled thermal-chemical models indicate that sub-Neptunes formed outside the water-ice line exhibit high atmospheric CH4, H2O, and C/O ratios while those formed inside show suppressed CH4 and low C/O.
Tier 1 Ariel spectra suffice for sub-1.5 dex constraints on H2O and CO2 in giant-planet atmospheres, with higher tiers providing only incremental gains and more molecules in select cases.
Discovery and orbital/stellar characterization of transiting brown dwarf TOI-6884b using TESS photometry corrected by ground-based RV and multi-epoch photometry.
SKA will detect emission from heavy molecules and prebiotic species in obscured disk regions to constrain initial chemical conditions for planet formation.
The paper reviews ML applications for sequence modeling, pattern recognition, and generative Bayesian analysis to tackle heterogeneous data challenges in (exo)planetary science.
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Coupling magma-ocean and atmospheres in spectral retrievals of sub-Neptunes
MELTYQ couples magma-atmosphere equilibrium models with spectral retrievals to constrain sub-Neptune magma oxidation states and volatile inventories from transmission spectra.
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Coupled Thermal-Chemical Evolution Models of Sub-Neptunes Reveal Atmospheric Signatures of Their Formation Location
Coupled thermal-chemical models indicate that sub-Neptunes formed outside the water-ice line exhibit high atmospheric CH4, H2O, and C/O ratios while those formed inside show suppressed CH4 and low C/O.
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TOI-6884b: A low-mass brown dwarf transiting a slightly evolved star
Discovery and orbital/stellar characterization of transiting brown dwarf TOI-6884b using TESS photometry corrected by ground-based RV and multi-epoch photometry.
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Unveiling Complex Chemistry in Planet-forming Disks with the SKAO
SKA will detect emission from heavy molecules and prebiotic species in obscured disk regions to constrain initial chemical conditions for planet formation.
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Machine Learning as a Transformative Tool for (Exo-)Planetary Science
The paper reviews ML applications for sequence modeling, pattern recognition, and generative Bayesian analysis to tackle heterogeneous data challenges in (exo)planetary science.