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High-Resolution Transmission Spectroscopy of the Terrestrial Exoplanet GJ 486b: Clouds and Hazes

by Exoplanetology Tech: Research on the Study of PlanetsFebruary 19th, 2024

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The exoplanet GJ 486b, orbiting an M3.5 star, is expected to have one of the strongest transmission spectroscopy signals among known terrestrial exoplanets.

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This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Andrew Ridden-Harper, Department of Astronomy and Carl Sagan Institute, Cornell University & Las Cumbres Observatory;

(2) Stevanus K. Nugroho, Astrobiology Center & Japan & National Astronomical Observatory of Japan;

(3) Laura Flagg, Department of Astronomy and Carl Sagan Institute, Cornell University;

(4) Ray Jayawardhana, Department of Astronomy, Cornell University;

(5) Jake D. Turner, Department of Astronomy and Carl Sagan Institute, Cornell University & NHFP Sagan Fellow;

(6) Ernst de Mooij, Astrophysics Research Centre, School of Mathematics and Physics & Queen’s University Belfast;

(7) Ryan MacDonald, Department of Astronomy and Carl Sagan Institute;

(8) Emily Deibert, David A. Dunlap Department of Astronomy & Astrophysics, University of Toronto & Gemini Observatory, NSF’s NOIRLab;

(9) Motohide Tamura, Dunlap Institute for Astronomy & Astrophysics, University of Toronto

(10) Takayuki Kotani, Department of Astronomy, Graduate School of Science, The University of Tokyo, Astrobiology Center & National Astronomical Observatory of Japan;

(11) Teruyuki Hirano, Astrobiology Center, National Astronomical Observatory of Japan & Department of Astronomical Science, The Graduate University for Advanced Studies;

(12) Masayuki Kuzuhara, Las Cumbres Observatory & Astrobiology Center;

(13) Masashi Omiya, Las Cumbres Observatory & Astrobiology Center;

(14) Nobuhiko Kusakabe, Las Cumbres Observatory & Astrobiology Center.

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7. CLOUDS AND HAZES

Clouds and hazes may be present in a wide range of exoplanet atmospheres (e.g., Helling 2019) and tend to suppress spectral features in exoplanet transmission spectra (e.g., Sing et al. 2016; Gandhi et al. 2020). As our models did not account for clouds (see Section 4), the constraints presented in Section 6.2 are only valid under the assumption that GJ 486b’s atmosphere is clear (i.e., free of clouds and haze).

To assess how our results would change without this assumption, we examined the effect of adding gray cloud decks at varying pressure levels to our hydrogendominated model with water at solar abundances (see Section 4). These models have cloud decks at pressures of 10−6 bar to 10−2 bar with factors of 10 between steps. As all the models used in this study set the planet radius to correspond to a pressure of 10−2 bar, the model with

a cloud deck at this level is essentially cloud-free. These models are shown before and after continuum subtraction in the top left and right panels of Fig. 13. We find that lower cloud deck pressures (corresponding to higher altitudes) result in more suppression of the spectral lines. To quantify the level of suppression caused by the clouds, we calculated auto-cross-correlation functions for each model. The lower left and right panels of Fig. 13 show the auto-cross-correlation functions and peak auto-cross-correlation amplitude, respectively, after normalizing so that the maximum value is 1. By comparing to the reference model with a cloud deck at 10−2 bar (essentially cloud-free), we find that cloud decks at pressures of .10−3 bar reduce the strength of the cross-correlation signal by a factor of &3. This implies that, if an injection/recovery test were performed (as in Section 6.2) with a cloudy model, it would be recovered to a lower significance than the same model without clouds. Therefore, some of the VMR-MMW parameter space that was ruled out by our data while assuming a clear atmosphere will still be allowed for a cloudy atmosphere.