A Modular Framework for Studying Neutron Star Structure and Cooling, with Dark Matter Applications

Abstract

Numerical modeling of neutron star cooling under full general relativity is treated with a new numerical framework in Python, capable of describing both neutron star structure and cooling for a given equation of state (EoS). The framework is developed with a heavy emphasis on flexibility and modular, simple code, facilitating both easy expandability in a gradual and consistent fashion, and simple comparison of a wide range of different models. The ease of using the framework to study and learn about neutron stars, combined with the simple way of including new physics to the model in the logically structured code, probably makes the framework one of a kind. Multiple EoS models are developed, and results obtained for both structure and cooling are in good agreement with qualitative and quantitative comparisons to other detailed works. We've also applied the most realistic models found to a cooling scenario including an exciting temperature-independent heating mechanism driven by annihilation of dark matter particles (WIMPs) in the interior, resulting in a stable minimum temperature plateau for neutron stars that has cooled for timescales of t ~ 10^7 yrs.