A Nuclear Equation of State Inferred from Stellar r-Process Abundances: Data

This repository contains the raw MCMC posteriors as H5 files for the three cases presented in "A Nuclear Equation of State Inferred from Stellar r-Process Abundances" (Holmbeck et al., arXiv:2110.06432).

Also included are Python scripts with a variety of functions to read the H5 files and interpret the data with LALSuite. These include:

reading the data contained in the H5 file (likelihood, acceptance, and values for each MCMC step)

generating a corner plot of the data

finding the maximum likelihood in the posterior distribution

calculating a neutron star mass-radius curve for a posterior EOS

calculating pressure and density for a posterior EOS

calculating observables (M_TOV, R_1.4, and L) associated with an EOS

The scripts are written for Python3 compatibility and depend on:

lalsuite

h5py

numpy

scipy

matplotlib

corner

For more information and how to use these scripts, see the comments in `example.py` or contact Erika Holmbeck.

If any of our posterior samples are used in your work, we ask that you appropriately cite this repository and the original paper (Holmbeck et al., arXiv:2110.06432).