**commit** f5072f60d948a38368b521640cfcbfd28937b490
**parent** 4aa638bf13c66dee81bf9d952bb64576b62346a5
**Author:** NicholasFarrow <nicholas.w.farrow@gmail.com>
**Date:** Thu, 7 Feb 2019 00:39:30 +1100
README changes
**Diffstat:**

1 file changed, 2 insertions(+), 2 deletions(-)

**diff --git a/README.md b/README.md**
@@ -1,5 +1,5 @@
# The mass distribution of Galactic double neutron stars
-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), one recycled NS and one 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.
+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](https://github.com/NicholasFarrow/GalacticDNSMass/blob/master/inferenceDemo.ipynb) or you can download the git repository with:
@@ -16,4 +16,4 @@ We highly recommend reading `<arxiv link>` along with this demonstraion.
* PyMultiNest (see https://johannesbuchner.github.io/PyMultiNest/install.html)
## Full code
-A more detailed version of the code can be found here under [mainCode](/mainCode/)
+A more detailed version of the code can be found here under [mainCode](/mainCode/).