VULCAN: An Open-source, Validated Chemical Kinetics Python Code for Exoplanetary Atmospheres

Abstract

We present an open-source and validated chemical kinetics code for studying hot exoplanetary atmospheres, which we name VULCAN. It is constructed for gaseous chemistry from 500 to 2500 K, using a reduced C-H-O chemical network with about 300 reactions. It uses eddy diffusion to mimic atmospheric dynamics and excludes photochemistry. We have provided a full description of the rate coefficients and thermodynamic data used. We validate VULCAN by reproducing chemical equilibrium and by comparing its output versus the disequilibriumchemistry calculations of Moses et al. and Rimmer & Helling. It reproduces the models of HD 189733b and HD 209458b by Moses et al., which employ a network with nearly 1600 reactions. We also use VULCAN to examine the theoretical trends produced when the temperature-pressure profile and carbon-to-oxygen ratio are varied. Assisted by a sensitivity test designed to identify the key reactions responsible for producing a specific molecule, we revisit the quenching approximation and find that it is accurate for methane but breaks down for acetylene, because the disequilibrium abundance of acetylene is not directly determined by transport-induced quenching, but is rather indirectly controlled by the disequilibrium abundance of methane. Therefore we suggest that the quenching approximation should be used with caution and must always be checked against a chemical kinetics calculation. A one-dimensional model atmosphere with 100 layers, computed using VULCAN, typically takes several minutes to complete. VULCAN is part of the Exoclimes Simulation Platform (ESP; exoclime.net) and publicly available at https://github.com/exoclime/VULCAN.

The effect of metallicity on the atmospheres of exoplanets with fully coupled 3D hydrodynamics, equilibrium chemistry, and radiative transfer

“…Physical processes, such as mixing and photochemistry, have been shown to drive the chemistry out of equilibrium using 1D (e.g. Liang et al 2003;Line et al 2010;Moses et al 2011;Venot et al 2012;Zahnle & Marley 2014;Drummond et al 2016;Tsai et al 2017), psuedo-2D (Agúndez et al 2014a) and simplified 3D (Cooper & Showman 2006) models. Non-equilibrium chemistry has also been suggested to explain discrepancies between observations and models that assume chemical equilibrium (e.g.…”

Implications of three-dimensional chemical transport in hot Jupiter atmospheres: Results from a consistently coupled chemistry-radiation-hydrodynamics model

“…Chemical iterations continue until either the integration time is equal to the set chemical timestep or the chemical system has reached a steady-state. Steady-state is assessed via the maximum relative change in the number densities of the individual species in an approach similar to Tsai et al (2017). We find that continuing iterations significantly beyond the point at which the system has reached a steady-state can lead to numerical errors.…”

“…Since the early work of Liang et al (2003) the trend has been for such networks to grow in size and complexity. However, more recently the focus has shifted to the development of smaller chemical networks (Tsai et al 2017;Venot et al 2019a) that are less computationally demanding, making them feasible for use in a 3D atmosphere model. We use the "reduced" chemical network recently developed by Venot et al (2019a).…”

Atmospheric compositions and observability of nitrogen-dominated ultra-short-period super-Earths

“…We note that other effects, such as condensation and surface exchange, as well as atmospheric escape could impact the chemistry and will be considered in the follow up studies (see Section 4). To generate these model atmospheres, we use the open source chemical kinetics code VULCAN 1 (Tsai et al 2017) which solves the one-dimensional continuity equation for 4 different elements (N, H, C, O) and over 50 molecular species. We employ the reduced NCHO network from VUL-CAN, consisting of 617 reactions (including reversed), with an additional 35 photodissociation reactions.…”

“…The forward reaction rates are obtained mostly from the NIST database 2 . The reverse reaction rates are computed using NASA polynomial thermodynamics data 3 (see Tsai et al 2017, for the full, non-photochemical reactions list and a more detailed description of the model).…”