Chemical complexity in astrophysical simulations: Optimization and reduction techniques

Abstract

Chemistry plays a key role in the evolution of the interstellar medium, so it is highly important to follow its evolution in numerical simulations. However, it could easily dominate the computational cost when applied to large systems. In this paper we discuss two approaches to reduce these costs: (i) based on computational strategies, and (ii) based on the properties and on the topology of the chemical network. The first methods are more robust, while the second are meant to be giving important information on the structure of large, complex networks.We first discuss the numerical solvers for integrating the system of ordinary differential equations (ODE) associated with the chemical network, and then we propose a buffer method that decreases the computational time spent in solving the ODE system. We further discuss a flux-based method that allows one to determine and then cut on the fly the less active reactions.In addition we also present a topological approach for selecting the most probable species that will be active during the chemical evolution, thus gaining information on the chemical network that otherwise would be difficult to retrieve. This topological technique can also be used as an a priori reduction method for any size network.We implemented these methods into a 1D Lagrangian hydrodynamical code to test their effects: both classes lead to large computational speed-ups, ranging from ×2 to ×5. We have also tested some hybrid approaches finding that coupling the flux method with a buffer strategy gives the best trade-off between robustness and speed-up of calculations. © 2013 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.