Reproducibility package for: "Nuclear Neural Networks: Emulating late burning stages in Core Collapse Supernova Progenitors"
Contributors
- 1. University of Arizona
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2.
Michigan State University
- 3. Max Planck Institute for Astrophysics
- 4. University of Amsterdam
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5.
Yale University
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6.
Los Alamos National Laboratory
Description
Reproducibility package for: "Nuclear Neural Networks: Emulating late burning stages in Core Collapse Supernova Progenitors". It contains mesa stellar models used to determine the parameter space of the training sets, training sets, trained nuclear neural network (NNN) models, test datasets, and python scripts used for the analysis performed in this manuscript, including scripts and result files used to generate the figures. Detailed documentation on how to reproduce our results, along with guidelines on how to use and/or create NNNs for your own science can be found in this guide. The complete BBQ runs that include additional timesteps for training the NNNs and datasets for extended density ranges, comprising a total of 4TB, will be shared upon request from the corresponding author.
Files
NuclearNeuralNetworks.zip
Files
(49.1 GB)
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md5:ab31e56950e696aba7747f2cfca2d403
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md5:e560d6dfab6a48df98e39d67874bddf1
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Additional details
Dates
- Submitted
-
2025-02-24