Retrieving scattering clouds and disequilibrium chemistry in the atmosphere of HR 8799e
P. Molli\`ere, T. Stolker, S. Lacour, G. P. P. L. Otten, J. Shangguan,, B. Charnay, T. Molyarova, M. Nowak, Th. Henning, G.-D. Marleau, D. A., Semenov, E. van Dishoeck, F. Eisenhauer, P. Garcia, R. Garcia Lopez, J. H., Girard, A. Z. Greenbaum, S. Hinkley, P. Kervella

TL;DR
This study develops a flexible retrieval framework to analyze exoplanet atmospheres, successfully constraining the C/O ratio of HR 8799e and demonstrating the importance of cloud modeling and disequilibrium chemistry in spectral interpretation.
Contribution
It introduces a new retrieval approach coupling radiative transfer with multiple scattering, testing different cloud models, and applying it to directly imaged exoplanets to robustly determine atmospheric composition.
Findings
The atmosphere of HR 8799e is cloudy with disequilibrium chemistry.
The C/O ratio of HR 8799e is approximately 0.60, consistent across models.
Retrievals are feasible with current high-sensitivity instruments.
Abstract
Clouds are ubiquitous in exoplanet atmospheres and represent a challenge for the model interpretation of their spectra. Complex cloud models are too numerically costly for generating a large number of spectra, while more efficient models may be too strongly simplified. We aim to constrain the atmospheric properties of the directly imaged planet HR 8799e with a free retrieval approach. We use our radiative transfer code petitRADTRANS for generating spectra, which we couple to the PyMultiNest tool. We added the effect of multiple scattering which is important for treating clouds. Two cloud model parameterizations are tested: the first incorporates the mixing and settling of condensates, the second simply parameterizes the functional form of the opacity. In mock retrievals, using an inadequate cloud model may result in atmospheres that are more isothermal and less cloudy than the input.…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
