Helios-r2 -- A new Bayesian, open-source retrieval model for brown dwarfs and exoplanet atmospheres
Daniel Kitzmann, Kevin Heng, Maria Oreshenko, Simon L. Grimm, Daniel, Apai, Brendan P. Bowler, Adam J. Burgasser, Mark S. Marley

TL;DR
Helios-r2 is an open-source, hybrid CPU-GPU atmospheric retrieval code designed for medium-resolution spectra of brown dwarfs and exoplanets, validated through various tests and applied to benchmark objects.
Contribution
The paper introduces Helios-r2, a new Bayesian atmospheric retrieval model that improves upon previous methods and is suitable for upcoming JWST data, with extensive validation and open-source availability.
Findings
Helios-r2 accurately retrieves surface gravities consistent with prior studies.
Calibration factors help account for uncertainties in physical parameters.
Results depend on assumptions about chemical equilibrium.
Abstract
We present an improved, hybrid CPU-GPU atmospheric retrieval code, Helios-r2, which is applicable to medium-resolution emission spectra of brown dwarfs, in preparation for precision atmospheric spectroscopy in the era of the James Webb Space Telescope. The model is available as open-source code on the Exoclimes Simulation Platform. We subject Helios-r2 to a battery of tests of varying difficulty. The simplest test involves a mock retrieval on a forward model generated using the same radiative transfer technique, the same implementation of opacities, and the same chemistry model. The least trivial test involves a mock retrieval on synthetic spectra from the Sonora model grid, which uses a different radiative transfer technique, a different implementation of opacities, and a different chemistry model. A calibration factor, which is included to capture uncertainties in the brown dwarf…
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