Bayesian Uncertainty Quantification of the Infinite Nuclear Matter Equation of State

This repository contains the data and Jupyter notebooks to produce the figures in our publications:

• Drischler, Furnstahl, Melendez, and Phillips, How well do we know the neutron-matter equation of state at the densities inside neutron stars? A Bayesian approach with correlated uncertainties, arXiv:2004.07232.

• Drischler, Melendez, Furnstahl, and Phillips, Effective Field Theory Convergence Pattern of Infinite Nuclear Matter, arXiv:2004.07805.

Overview

The directory analysis contains all the relevant Jupyter notebooks, including the main notebooks derivatives-bands.ipynb and correlated_matter_analysis_refactored.ipynb, which generate the figures in our papers. The directories nuclear_matter and other_figures contain the raw Python implementation, helper functions, etc. and additional figures not shown in the papers (e.g., for talks). The raw data for the equation of state of neutron matter and symmetric nuclear matter can be found in data and raw_data. More information can be found in the README files as well as in the annotated notebooks.

Requirements and Installations

Installing and running our Jupyter notebooks is straightforward. Python 3 is required with the (standard) packages listed in requirements.txt installed. They can be installed by running the command:

pip3 install -r requirements.txt

In addition, J. Melendez's package gsum, which is publicly available here including installation instructions, needs to be installed separately. Do not use gsum as installed by pip3.

With these prerequisites, to install this repository simply run (at the top level):

pip3 install .

Symmetry Energy and its Slope Parameter

BUQEYE's version of J. Lattimer's well-known Sv--L plot, Figure 2 of our arXiv:2004.07232, can be produced using the Jupyter Notebook analysis/Esym-L/Esym_L_correlation_plot.ipynb. In addition to a static pdf file, we support the export of an animated gif, which shows the different empirical constraints incrementally. This is, in particular, useful for scientific talks and teaching.

Contact

To report any issues please use the issue tracker.

Citing this Work and Further Reading

• Drischler, Furnstahl, Melendez, and Phillips, How well do we know the neutron-matter equation of state at the densities inside neutron stars? A Bayesian approach with correlated uncertainties, arXiv:2004.07232.

• Drischler, Melendez, Furnstahl, and Phillips, Effective Field Theory Convergence Pattern of Infinite Nuclear Matter, arXiv:2004.07805.