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ExoReL^R: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra

Damiano, Mario and Hu, Renyu (2020) ExoReL^R: A Bayesian Inverse Retrieval Framework for Exoplanetary Reflected Light Spectra. Astronomical Journal, 159 (4). Art. No. 175. ISSN 1538-3881. https://resolver.caltech.edu/CaltechAUTHORS:20200331-123159559

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Abstract

The high-contrast imaging technique is meant to provide insight into those planets orbiting several astronomical units from their host star. Space missions such as Wide-Field InfraRed Survey Telescope, Habitable Exoplanet Imaging Mission, and Large Ultra-Violet/Optical/InfraRed Surveyor will measure reflected light spectra of cold gaseous and rocky planets. To interpret these observations, we introduce EXOREL^R (Exoplanetary Reflected Light Retrieval), a novel Bayesian retrieval framework to retrieve cloud properties and atmospheric structures from exoplanetary reflected light spectra. As a unique feature, it assumes a vertically nonuniform volume mixing ratio (VMR) profile of water and ammonia, and uses it to construct cloud densities. In this way, clouds and molecular mixture ratios are consistent. We apply EXOREL^R on three test cases: two exoplanets (υ And e and 47 Uma b) and Jupiter. We show that we are able to retrieve the concentration of methane in the atmosphere, and estimate the position of clouds when the signal-to-noise ratio of the spectrum is higher than 15, in line with previous works. Moreover, we described the ability of our model to give a chemical identity to clouds, and we discussed whether or not we can observe this difference in the planetary reflection spectrum. Finally, we demonstrate how it could be possible to retrieve molecular concentrations (water and ammonia in this work) below the clouds by linking the nonuniform VMR profile to the cloud presence. This will help to constrain the concentration of water and ammonia unseen in direct measurements.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3847/1538-3881/ab79a5DOIArticle
https://arxiv.org/abs/2003.01814arXivDiscussion Paper
ORCID:
AuthorORCID
Damiano, Mario0000-0002-1830-8260
Hu, Renyu0000-0003-2215-8485
Additional Information:© 2020 The American Astronomical Society. Received 2019 September 12; revised 2020 January 27; accepted 2020 February 22; published 2020 March 30. The authors thank Dr. Graça M. Rocha and Dr. Sergi R. Hildebrandt for helpful discussions, materials, and encouragement in the preparation of this manuscript. This work was supported in part by the NASA WFIRST Preparatory Science grant #NNN13D460T, and NASA WFIRST Science Investigation Teams grant #NNN16D016T. The research was carried out at the California Institute of Technology Jet Propulsion Laboratory. This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.
Funders:
Funding AgencyGrant Number
NASANNN13D460T
NASANNN16D016T
NASA/JPL/CaltechUNSPECIFIED
Subject Keywords:Planetary science ; Planetary atmospheres ; Bayesian statistics ; Exoplanets ; Extrasolar gas giants ; Radiative transfer ; Spectroscopy
Issue or Number:4
Classification Code:Unified Astronomy Thesaurus concepts: Planetary science (1255); Planetary atmospheres (1244); Bayesian statistics (1900); Exoplanets (498); Extrasolar gas giants (509); Radiative transfer (1335); Spectroscopy (1558)
Record Number:CaltechAUTHORS:20200331-123159559
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200331-123159559
Official Citation:Mario Damiano and Renyu Hu 2020 AJ 159 175
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:102201
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:31 Mar 2020 19:44
Last Modified:31 Mar 2020 19:44

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