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YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds
被引:7
|作者:
Ma, Sushuang
[1
]
Ito, Yuichi
[1
,2
]
Al-Refaie, Ahmed Faris
[1
]
Changeat, Quentin
[1
,3
]
Edwards, Billy
[1
,4
,5
]
Tinetti, Giovanna
[1
]
机构:
[1] UCL, Dept Phys & Astron, Gower St, London WC1E 6BT, England
[2] Natl Astron Observ Japan, 2 Chome-21-1, Mitaka, Tokyo 1818588, Japan
[3] European Space Agcy ESA ESA Off, Space Telescope Sci Inst STScI, 3700 San Martin Dr, Baltimore, MD 21218 USA
[4] SRON Netherlands Inst Space Res, SRON, Niels Bohrweg 4, NL-2333 CA Leiden, Netherlands
[5] Univ Paris, Univ Paris Saclay, AIM, CEA,CNRS, F-91191 Gif Sur Yvette, France
关键词:
DESCRIBING AEROSOL FORMATION;
RADIATIVE-TRANSFER;
HIGH-RESOLUTION;
BROWN DWARFS;
CONDENSATION CLOUDS;
EMISSION-SPECTRA;
GIANT EXOPLANETS;
ATMOSPHERES;
MODEL;
JUPITER;
D O I:
10.3847/1538-4357/acf8ca
中图分类号:
P1 [天文学];
学科分类号:
0704 ;
摘要:
In this paper, we present YunMa, an exoplanet cloud simulation and retrieval package, which enables the study of cloud microphysics and radiative properties in exoplanetary atmospheres. YunMa simulates the vertical distribution and sizes of cloud particles and their corresponding scattering signature in transit spectra. We validated YunMa against results from the literature. When coupled to the TauREx 3 platform, an open Bayesian framework for spectral retrievals, YunMa enables the retrieval of the cloud properties and parameters from transit spectra of exoplanets. The sedimentation efficiency (f sed), which controls the cloud microphysics, is set as a free parameter in retrievals. We assess the retrieval performances of YunMa through 28 instances of a K2-18 b-like atmosphere with different fractions of H2/He and N2, and assuming water clouds. Our results show a substantial improvement in retrieval performances when using YunMa instead of a simple opaque cloud model and highlight the need to include cloud radiative transfer and microphysics to interpret the next-generation data for exoplanet atmospheres. This work also inspires instrumental development for future flagships by demonstrating retrieval performances with different data quality.
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页数:19
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