A Fast, Parallelized, GPU-Accelerated Photochemical Model, XODIAC, with Built-in Equilibrium Chemistry and Multiple Chemical Networks for Exoplanetary Atmospheres

TL;DR

XODIAC delivers a fast, GPU-accelerated 1D photochemical model with built-in equilibrium chemistry and multiple networks to enable robust comparative exoplanetary atmospheric studies. The paper introduces the XODIAC-2025 network (7720 reactions, 594 species) and a new thermochemical database, validated against ARGO and VULCAN for HD 189733 b, with results showing strong cross-model agreement when networks and initial conditions are held constant. A detailed comparison across three networks reveals notable, chemistry-specific differences, especially in phosphorus chemistry, underscoring the importance of network completeness for accurate predictions. The work demonstrates scalable CPU/GPU parallelization and provides a flexible framework for future, larger chemical networks and broader classes of exoplanets, advancing the field of comparative exoplanetology.

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 rigorously benchmarked on the well-studied hot Jupiter HD 189733 b, with results compared against these two models. Benchmarking shows excellent agreement and demonstrates that, when the same chemical network and initial conditions are used, the numerical scheme for solving atmospheric chemistry does not significantly affect the results. We also revisited the atmospheric chemistry of HD 189733 b and performed a comparative analysis across the three networks. Sulfur chemistry shows the least variation across networks, carbon chemistry shows slightly more, and phosphorus chemistry varies the most, primarily due to the introduction of unique PHO and PN pathways comprising 390 reactions in the XODIAC-2025 network. These findings highlight XODIAC's capability to advance exoplanetary atmospheric chemistry and provide a robust framework for comparative exoplanetology.

Figures (12)

• Figure 1: Schematic overview of XODIAC, illustrating the available options for initial composition, chemical networks, pressure–temperature (P–T) profiles, eddy diffusion ($k_{zz}$), actinic flux, and planetary parameters. The model employs a Lagrangian methodology and an ODE solver to compute species volume mixing ratio (VMR) profiles until convergence.
• Figure 2: The figure shows the movement of an air parcel in a one-dimensional atmosphere transitioning from the lower atmosphere up to the higher atmosphere with volume mixing ratio (VMR) varying due to molecular diffusion, vertical mixing, photochemistry, and atmospheric escape.
• Figure 3: Pressure–temperature and eddy diffusion coefficient ($K_{\mathrm{zz}}$) profile of HD 189733 b (adopted from Mosses_2011)
• Figure 4: Comparison between XODIAC (solid lines) and ARGO (dotted lines) using the STAND-2020 reaction network for HD 189733b, showing species containing S, N, C, H, and O.
• Figure 5: Comparison between XODIAC (solid lines) and VULCAN (dotted line) with the VULCAN-SNCHO reaction network for HD 189733b, showing species containing S, N, C, H, and O.