pynucastro: A python library for connecting nuclear data to astrophysical simulations

Stellar evolution is driven by the changing composition of a star from

nuclear reactions. During most of their lives, this change is slow

and the energy released from reactions in their interior is radiated

through their surface. At late stages of their evolution, or when

interacting with binary companions, the energy release can be fast

and drive stellar explosions. Modeling reacting stellar flows

requires coupling a hydrodynamic simulation code with a nuclear

reaction network, with attention to modern supercomputer programming

models.

Often in simulations, we would like to explore how our results are

sensitive to the details of the nuclear physics: the size of the

network, rates used, screening formulations, etc. To aid in this

exploration, we've created a python library, pynucastro, that can

interface with nuclear data resources and allow for interactive

exploration of rates and networks, as well as output C++ or python

code corresponding to the righthand side of the system of ordinary

differential equations that needs to be evolved to model the

reactions. This framework makes it easy to produce new networks and

adapt to updates in reaction rates of other nuclear physics.

We describe the features of pynucastro, including the libraries of

rates it currently uses, and show how to export a network to be used

with GPU acceleration in our simulation code, Castro. Example

simulations of Type Ia supernovae, X-ray bursts, and massive star

convection leading up to core-collapse will be shown. All of the

code is fully open source and follows a community development model.