Impact of an accurate modeling of primordial chemistry in high resolution studies

TL;DR

This study demonstrates that high-accuracy modeling of primordial chemistry and thermodynamics in high-resolution simulations leads to more reliable and convergent results in the formation of the first stars.

Contribution

The paper compares different numerical methods for modeling chemistry and thermodynamics, showing that higher-order solvers improve robustness in primordial star formation simulations.

Findings

Higher-order BDF solver yields more consistent results across resolutions.

Standard methods show resolution-dependent variations in temperature and density.

Accurate chemistry modeling is crucial for realistic primordial star formation simulations.

Abstract

The formation of the first stars in the Universe is regulated by a sensitive interplay of chemistry and cooling with the dynamics of a self-gravitating system. As the outcome of the collapse and the final stellar masses depend sensitively on the thermal evolution, it is necessary to accurately model the thermal evolution in high resolution simulations. As previous investigations raised doubts regarding the convergence of the temperature at high resolution, we investigate the role of the numerical method employed to model the chemistry and the thermodynamics. Here we compare the standard implementation in the adaptive-mesh refinement code \verb|ENZO|, employing a first order backward differentiation formula (BDF), with the 5th order accurate BDF solver \verb|DLSODES|. While the standard implementation in \verb|ENZO| shows a strong dependence on the employed resolution, the results obtained with \verb|DLSODES| are considerably more robust, both with respect to the chemistry and thermodynamics, but also for dynamical quantities such as density, total energy or the accretion rate. We conclude that an accurate modeling of the chemistry and thermodynamics is central for primordial star formation.