A Fast, Parallelized, GPU-Accelerated Photochemical Model, XODIAC, with Built-in Equilibrium Chemistry and Multiple Chemical Networks for Exoplanetary Atmospheres
Priyankush Ghosh, Sambit Mishra, Shubham Dey, Debayan Das, Paul B. Rimmer, Liton Majumdar

TL;DR
XODIAC is a GPU-accelerated, flexible photochemical model for exoplanet atmospheres, enabling rapid, comparative studies with multiple chemical networks and validated against existing models on hot Jupiter data.
Contribution
The paper introduces XODIAC, a novel, fast, GPU-based photochemical model with built-in equilibrium chemistry and multiple networks, including a new comprehensive C-H-O-N-P-S-Metals network.
Findings
XODIAC shows excellent agreement with established models on HD 189733 b.
Chemical network choice affects phosphorus chemistry most significantly.
Benchmarking confirms numerical scheme consistency across models.
Abstract
The launch of the James Webb Space Telescope (JWST) has delivered high-quality atmospheric observations and expanded the known chemical inventory of exoplanetary atmospheres, opening new avenues for atmospheric chemistry modeling to interpret these data. Here, we present XODIAC, a fast, GPU-accelerated, one-dimensional photochemical model with a built-in equilibrium chemistry solver, an updated thermochemical database, and three chemical reaction networks. This framework enables comparative atmospheric chemistry studies, including the newly developed XODIAC-2025 network, a state-of-the-art C-H-O-N-P-S-Metals network, linking 594 species through 7,720 reactions. The other two are existing, publicly available C-H-O-N-S and C-H-O-N-S-Metals networks, from the established photochemical models VULCAN and ARGO, respectively, which are commonly used in the community. The XODIAC model has been…
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Taxonomy
TopicsStellar, planetary, and galactic studies · Astro and Planetary Science · Astronomy and Astrophysical Research
