The mass distribution of Galactic double neutron stars

We highly recommend reading The Mass Distribution of Galactic Double Neutron Stars; (Farrow, Zhu, & Thrane 2019) for details along with this demonstraion.

Here we provide code which performs Bayesian inference on a sample of 17 Galactic double neutron stars (DNS) in order to investigate their mass distribution. Each DNS is comprised of two neutron stars (NS), a recycled NS and a non-recycled (slow) NS. We compare two hypotheses: A - recycled NS and non-recycled NS follow an identical mass distribution, and B - they are drawn from two distinct populations. Within each hypothesis we also explore three possible functional models: gaussian, two-gaussian (mixture model), and uniform mass distributions.

You can take a look at the demo here or you can download the git repository with:

git clone https://github.com/NicholasFarrow/GalacticDNSMass.

Requirements

Without running inference (just demonstration & data analysis):

• Jupyter or Ipython
• numpy, scipy

Additional requirements if performing own inference:

• PyMultiNest (see https://johannesbuchner.github.io/PyMultiNest/install.html)

Full code

A more detailed version of the code can be found here under mainCode.

Citations

Thank you Buchner et al. 2014, A&A for their python interface of MultiNest F. Feroz, M.P. Hobson, M. Bridges. 2008