Fully scalable forward model grid of exoplanet transmission spectra. Issue 4 (3rd November 2018)

• Record Type: Journal Article
• Authors: Goyal, Jayesh M; Wakeford, Hannah R; Mayne, Nathan J; Lewis, Nikole K; Drummond, Benjamin; Sing, David K
• Is Part Of: Monthly notices of the Royal Astronomical Society. Volume 482:Issue 4(2019)
• Page Start: 4503
• Page End: 4513
• Publication Date: 2018-11-03
• Subjects: planets and satellites: atmospheres -- planets and satellites: composition -- techniques: spectroscopic; Astronomy -- Periodicals; Periodicals; 520.5
• DOI: 10.1093/mnras/sty3001
• Languages: English
• ISSNs: 0035-8711

Abstract

ABSTRACT: Simulated exoplanet transmission spectra are critical for planning and interpretation of observations and to explore the sensitivity of spectral features to atmospheric thermochemical processes. We present a publicly available generic model grid of planetary transmission spectra, scalable to a wide range of H2 /He dominated atmospheres. The grid is computed using the 1D/2D atmosphere model ATMO for two different chemical scenarios, first considering local condensation only, secondly considering global condensation and removal of species from the atmospheric column (rainout). The entire grid consists of 56 320 model simulations across 22 equilibrium temperatures (400–2600 K), four planetary gravities (5–50 ms −2 ), five atmospheric metallicities (1x–200x), four C/O ratios (0.35–1.0), four scattering haze parameters, four uniform cloud parameters, and two chemical scenarios. We derive scaling equations which can be used with this grid, for a wide range of planet–star combinations. We validate this grid by comparing it with other model transmission spectra available in the literature. We highlight some of the important findings, such as the rise of SO2 features at 100x solar metallicity, differences in spectral features at high C/O ratios between two condensation approaches, the importance of VO features without TiO to constrain the limb temperature and features of TiO/VO both, to constrain the condensation processes. Finally, this generic grid can be used to plan future observations using the HST, VLT, JWST, and various other telescopes. The fine variation of parameters in the grid also allows it to be incorporated in a retrieval framework, with various machine learning techniques.