Pre-computed aerosol extinction, scattering and asymmetry grids for scalable atmospheric retrievals

TL;DR

This paper introduces pre-computed aerosol property grids that significantly enhance the efficiency of atmospheric retrievals for exoplanet studies, enabling more complex analyses within practical time frames.

Contribution

It presents a novel method of pre-computing aerosol optical property grids, reducing computational costs and scaling efficiently with multiple condensate species in atmospheric retrievals.

Findings

Pre-computed grids reduce computation time by 1.4 to 17 times.

Negligible differences in retrieval accuracy with the new method.

Enables more complex and broader population studies.

Abstract

The unprecedented wavelength coverage and sensitivity of the James Webb Space Telescope (JWST) permits to measure the absorption features of a wide range of condensate species from Silicates to Titan tholins. Atmospheric retrievals are uniquely suited to analyse these datasets and characterize the aerosols present in exoplanet atmospheres. However, including the optical properties of condensed particles within retrieval frameworks remains computationally expensive, limiting our ability to fully exploit JWST observations. In this work, we improve the computational efficiency and scaling behavior of aerosol models in atmospheric retrievals, enabling in-depth studies including multiple condensate species within practical time scales. Rather than computing the aerosol Mie coefficients for each sampled model, we pre-compute extinction efficiency (Qext), scattering efficiency (Qscat) and asymmetry parameter (g) grids for seven condensate species relevant in exoplanet atmospheres (Mg2SiO4 amorph sol - gel, MgSiO3 amorph glass, MgSiO3 amorph sol - gel, SiO2 alpha, SiO2 amorph, SiO and Titan tholins). The pre-computed Qext grids significantly reduce computation time between 1.4 and 17 times with negligible differences on the retrieved parameters. They also scale effortlessly with the number of aerosol species while maintaining the accuracy of cloud models. Thereby enabling more complex retrievals as well as broader population studies without increasing the overall error budget. The Qext, Qscat and g grids are freely available on Zenodo as well as a public TauREx plugin -TauREx-PCQ- that utilize them.