Investigating the Influence of Mean-Opacity (𝜅) Values on Interior-Atmosphere Modelling

Ever since the discovery of sub-Neptunes, exoplanets with masses < 20 M⊕ and radii < 4 R⊕, they have presented a distinct challenge in the exoplanet modelling community. When plotted on a mass-radius diagram, their bulk densities lie in a range spanning from that of pure iron to less than water. Such bulk densities are not necessarily indicative of the interior structure within, and when characterized using interior models the results are often varied in their morphology and highly degenerate. 

 

A semi-grey pressure-temperature profile approximation for an atmosphere is a popular choice in Interior-Atmosphere modelling as could allow us to estimate the radius contribution of an atmosphere as well as a full radiative transfer line-by-line model, but without the computational cost of a full 1-D radiative convective climate-chemistry model. Since the parameter space is large, thousands of interior-atmosphere model runs are required in order to quantify the potential degeneracies. Nevertheless, while the semi-grey approximation treats the problem in a more simplified manner than other more robust methods, which allows for faster analytical calculations, there are still underdetermined factors which make choosing the most appropriate value difficult without more data (e.g. atmospheric spectra and profiles). 

 

In this talk I will explore the impact of the different ways one chooses the value of one factor, the mean-opacity (𝜅). As this is a function of the stellar and planetary radiation wavelengths, it has an effect on not only the atmospheric and planetary profiles, but also the range of characterization solutions and their degeneracies therein. To highlight these differences, I will be focussing on two real-world test cases: GJ 1214 b and K2-18 b, at two different atmospheric compositions (1x and 50x solar metallicity). By comparing the atmosphere profiles and the range of solutions from interior modelling, both within the parameter range and to values in literature, we will quantify the impact on planetary characterization and develop a more systematic method for future models.