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High-Resolution Transmission Spectroscopy of the Terrestrial Exoplanet GJ 486b: Model Spectraby@exoplanetology
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High-Resolution Transmission Spectroscopy of the Terrestrial Exoplanet GJ 486b: Model Spectra

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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.

4. MODEL SPECTRA

We searched for chemical species in GJ 486b’s atmosphere through a cross-correlation analysis with model transmission spectra. We generated a grid of template spectra using the open-source radiative transfer code petitRADTRANS[5] (Molli`ere et al. 2019). Each template contains one or more absorbing chemical species embedded in a background of spectrally inactive gas. Specifically, we searched for a wide range of gaseous absorbers: C2H2, CH4, CO, CO2, FeH, H2O, HCN, H2S, K, Na, NH3, PH3, SiO, TiO, and VO. We used the default opacity data included with petitRADTRANS (see Molli`ere et al. 2019) for all species. However, for CH4 we used both the default opacity data from Exomol (Yurchenko & Tennyson 2014) and our custom-made opacity grid based on a line list adopted from HITEMP 2020 (Hargreaves et al. 2020). We produced the custom opacity grid following the pressure-temperature grid in the petitRADTRANS website (e.g., PTgrid.dat). We calculated the cross section using HELIOS-K 2.0 (Grimm & Heng 2015; Grimm et al. 2021) with a line wing cutoff of 100 cm−1 at a resolution of 0.001 cm−1 which was later resampled at a constant resolution of R = 106 . Our templates include two chemical models: (i) single chemical species models and (ii) multispecies chemical equilibrium models.


Our single-species models span a range of volume mixing ratios (VMRs) and MMWs. The VMRs range from log10(VMR) = −7 to 0 (assumed constant with altitude). We varied the MMWs independently of the VMRs, subject to the following boundary conditions: (i) the minimum MMW corresponds to a H2-dominated atmosphere with the template species (i.e. MMWmin ≈ 2 · (1 − VMRi) + VMRi · MMWi); and (ii) the maximum MMW corresponds to an N2-dominated atmosphere with the template species (i.e. MMWmax ≈ 28 · (1 − VMRi) + VMRi · MMWi). These boundary conditions ensure the MMWs are physically consistent with the presence of a spectrally inactive gas mixture with unknown ratios of H2, He, or N2. These models assumed an isothermal pressure-temperature (P-T) profile at GJ 486b’s equilibrium temperature: 700 K (Trifonov et al. 2021).


Our second set of models included all the above mentioned spectrally active species with thermochemical equilibrium abundances. We computed equilibrium abundances for a solar composition atmosphere using the open-source code GGchem[6] (Woitke et al. 2018), assuming isothermal P-T profiles at 400, 500, 600, and 700 K. We considered three different approaches for modeling condensation in GGchem: (1) no condensation, (2) condensation included, and (3) condensation included, but condensates removed (e.g., rain out). These abundance profiles are shown in Fig. 1. Although condensation would likely result in the production of aerosols such as clouds or hazes, we do not attempt to account for the effect of such aerosols on the resulting transmission spectrum.


Our petitRADTRANS models were computed line by line at R = 106 using 130 layers spaced evenly in logpressure from 10−11 to 102 bar. We then resampled the model spectra to the resolution of the data (R = 45 k, 70 k, and 75 k for IGRINS, IRD, and SPIRou, respectively) using the SpectRes package[7] (Carnall 2017) which preserves the integrated flux. Because cross-correlations are not sensitive to continua, we subtracted the continuum from our model spectra (after binning to the data resolution) to produce our final cross-correlation templates.




[5] https://petitradtrans.readthedocs.io/en/latest/


[6] https://github.com/pw31/GGchem


[7] https://spectres.readthedocs.io/en/latest/