A Catalogue of Exoplanet Atmospheric Retrieval Codes
Authors/Creators
- 1. University of Michigan
- 2. NASA Ames Research Center
Description
Exoplanet atmospheric retrieval is a computational technique widely used to infer properties of planetary atmospheres from remote spectroscopic observations. Retrieval codes typically employ Bayesian sampling algorithms or machine learning approaches to explore the range of atmospheric properties (e.g., chemical composition, temperature structure, aerosols) compatible with an observed spectrum. Here, we provide a catalogue of the atmospheric retrieval codes published to date, alongside links to their respective code repositories where available.
This is the continually updated version of the retrieval code catalogue first published in Research Notes of the AAS (MacDonald & Batalha, 2023, Res. Notes AAS 7 54).
Additions, corrections, and feedback are welcome!
Please feel free to email them to: ryanjmac@umich.edu
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Retrieval_Catalogue_Apr_2023.pdf
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Additional details
Related works
- Is supplement to
- Journal article: 10.3847/2515-5172/acc46a (DOI)