ExoClouds - ARCiS

The ARCiS framework for Exoplanet Atmospheres
Modelling Philosophy and Retrieval
Michiel Min, Chris W. Ormel, Katy Chubb, Christiane Helling and Yui Kawashima

Download the appendix with the posterior distributions of all models

Aims: ARCiS, a novel code for the analysis of exoplanet transmission and emission spectra is presented. The aim of the modelling framework is to provide a tool able to link observations to physical models of exoplanet atmospheres.
Methods: The modelling philosophy chosen in this paper is to use physical and chemical models to constrain certain parameters while keeping free the parts where our physical understanding is still more limited. This approach, in between full physical modelling and full parameterisation, allows us to use the processes we understand well and parameterise those less understood. A Bayesian retrieval framework is implemented and applied to the transit spectra of a set of 10 hot Jupiters. The code contains chemistry and cloud formation and has the option for self consistent temperature structure computations.
Results: The code presented is fast and flexible enough to be used for retrieval and for target list simulations for e.g. JWST or the ESA Ariel missions. We present results for the retrieval of elemental abundance ratios using the physical retrieval framework and compare this to results obtained using a parameterised retrieval setup.
Conclusions: We conclude that for most of the targets considered the current dataset is not constraining enough to reliably pin down the elemental abundance ratios. We find no significant correlations between different physical parameters. We confirm that planets in our sample with a strong slope in the optical transmission spectrum are the planets where we find cloud formation to be most active. Finally, we conclude that with ARCiS we have a computationally efficient tool to analyse exoplanet observations in the context of physical and chemical models.

The ARCiS framework for Exoplanet Atmospheres
The Cloud Transport Model
Chris W. Ormel and Michiel Min

Context. Understanding of clouds is instrumental in interpreting current and future spectroscopic observations of exoplanets. Mod- elling clouds consistently is complex, since it involves many facets of chemistry, nucleation theory, condensation physics, coagulation, and particle transport.
Aims. To develop a simple physical model for cloud formation and transport, efficient and versatile enough that it can be used, in modular fashion for parameter optimization searches of exoplanet atmosphere spectra. In this work we present the cloud model and investigate the dependence of key parameters as the cloud diffusivity K and the nuclei injection rate Σ ̇ n on the planet’s observational characteristics.
Methods. The transport equations are formulated in 1D, accounting for sedimentation and diffusion. The grain size is obtained through a moment method. For simplicity, only one cloud species is considered and the nucleation rate is parametrized. From the resulting physical profiles we simulate transmission spectra covering the visual to mid-IR wavelength range.
Results. We apply our models towards KCl clouds in the atmosphere of GJ1214 b and towards MgSiO3 clouds of a canonical hot- Jupiter. We find that larger K increases the thickness of the cloud, pushing the τ = 1 surface to a lower pressure layer higher in the atmosphere. A larger nucleation rate also increases the cloud thickness while it suppresses the grain size. Coagulation is most important at high Σ ̇ n and low K. We find that the investigated combinations of K and Σ ̇ n greatly affect the transmission spectra in terms of the slope at near-IR wavelength (a proxy for grain size), the molecular features seen at ∼μm (which disappear for thick clouds, high in the atmosphere), and the 10 μm silicate feature, which becomes prominent for small grains high in the atmosphere. Conclusions. Clouds have a major impact on the atmospheric characteristics of hot-Jupiters, and models as those presented here are necessary to reveal the underlying properties of exoplanet atmospheres. The result of our hybrid approach – aimed to provide a good balance between physical consistency and computational efficiency – is ideal towards interpreting (future) spectroscopic observations of exoplanets.

Random sampling technique for ultra-fast computations of molecular opacities for exoplanet atmospheres
Michiel Min

Context. Opacities of molecules in exoplanet atmospheres rely on increasingly detailed line-lists for these molecules. The line lists available today contain for many species up to several billions of lines. Computation of the spectral line profile created by pressure and temperature broadening, the Voigt profile, of all of these lines is becoming a computational challenge.
Aims: We aim to create a method to compute the Voigt profile in a way that automatically focusses the computation time into the strongest lines, while still maintaining the continuum contribution of the high number of weaker lines.
Methods: Here, we outline a statistical line sampling technique that samples the Voigt profile quickly and with high accuracy. The number of samples is adjusted to the strength of the line and the local spectral line density. This automatically provides high accuracy line shapes for strong lines or lines that are spectrally isolated. The line sampling technique automatically preserves the integrated line opacity for all lines, thereby also providing the continuum opacity created by the large number of weak lines at very low computational cost.
Results: The line sampling technique is tested for accuracy when computing line spectra and correlated-k tables. Extremely fast computations ( 3.5 × 105 lines per second per core on a standard current day desktop computer) with high accuracy (≤1% almost everywhere) are obtained. A detailed recipe on how to perform the computations is given.