We describe pynucastro 2.0, an open source library for interactively creating and exploring astrophysical nuclear reaction networks. We demonstrate new methods for approximating rates and using detailed balance to create reverse rates, show how to build networks and determine whether they are appropriate for a particular science application, and discuss the changes made to the library over the past few years. Finally, we demonstrate the validity of the networks produced and share how we use pynucastro networks in simulation codes.
@article{arxiv.2210.09965,
title = {pynucastro: A Python Library for Nuclear Astrophysics},
author = {Alexander Smith Clark and Eric T. Johnson and Zhi Chen and Kiran Eiden and Donald E. Willcox and Brendan Boyd and Lyra Cao and Christopher J. DeGrendele and Michael Zingale},
journal= {arXiv preprint arXiv:2210.09965},
year = {2022}
}
Comments
Submitted to Astrophysical Journal notebooks to reproduce all figures are available via Zenodo DOI: https://zenodo.org/record/7202413