2018/04/13 by Joachim W. Stock, J. W. Stock, Daniel Kitzmann +3 · 2 citations
Earth and Planetary Sciences · Mathematics · Physics and Astronomy · #Advanced Chemical Physics Studies #Algebraic equation #Algorithm #Applied mathematics #Atmospheric Ozone and Climate #Code (set theory) #Computation #Computer program #Computer science #Convergence (economics) #Mathematics #Nonlinear system #Physics #Programming language #Quantum mechanics #Set (abstract data type) #Spectroscopy and Quantum Chemical Studies #astro-ph.EP #astro-ph.SR
paper · pdf · doi:10.1093/mnras/sty1531
Submitted to MNRAS, 11 pages, 5 figures
arxiv created 2018/04/13 · openalex publication_date 2018/06/08 · arxiv updated 2018/06/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
For the calculation of complex neutral/ionized gas-phase chemical equilibria, we present a semi-analytical, versatile, and efficient computer program, called FastChem. The applied method is based on the solution of a system of coupled non-linear (and linear) algebraic equations, namely the law of mass action and the element conservation equations including charge balance, in many variables. Specifically, the system of equations is decomposed into a set of coupled nonlinear equations in one variable each, which are solved analytically whenever feasible to reduce computation time. Notably, the electron density is determined by using the method of Nelder and Mead at low temperatures. The program is written in object-oriented C++ which makes it easy to couple the code with other programs, although a stand-alone version is provided. FastChem can be used in parallel or sequentially and is available under the GNU General Public License version 3 at https://github.com/exoclime/FastChem together with several sample applications. The code has been successfully validated against previous studies and its convergence behaviour has been tested even for extreme physical parameter ranges down to |100 K| and up to |1000 bar|. FastChem converges stable and robust in even most demanding chemical situations, which posed sometimes extreme challenges for previous algorithms.