pynucastro: A Python Library for Nuclear Astrophysics

Smith, Alexander I.; Johnson, Eric T.; Chen, Zhi; Eiden, Kiran; Willcox, Donald E.; Boyd, Brendan; Cao, Lyra; DeGrendele, Christopher J.; Zingale, Michael

doi:10.3847/1538-4357/acbaff

Title: pynucastro: A Python Library for Nuclear Astrophysics

Journal Article · 21 April 2023 · The Astrophysical Journal

DOI: https://doi.org/10.3847/1538-4357/acbaff · OSTI ID:1992334

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Stony Brook Univ., NY (United States)
Univ. of California, Berkeley, CA (United States)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
The Ohio State Univ., Columbus, OH (United States)
Univ. of California, Santa Cruz, CA (United States)

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 use 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.

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Research Organization:: Stony Brook Univ., NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Nuclear Physics (NP); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR). Scientific Discovery through Advanced Computing (SciDAC); USDOE National Nuclear Security Administration (NNSA); Chilean Government; US Department of State

Grant/Contract Number:: FG02-87ER40317; SC0017955; 56160017; PS00280789

OSTI ID:: 1992334

Journal Information:: The Astrophysical Journal, Vol. 947, Issue 2; ISSN 0004-637X

Publisher:: IOP PublishingCopyright Statement

Country of Publication:: United States

Language:: English

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