Adventures in inferring neutron-star-black-hole binary parameters

Code to simulate and analyse populations of neutron-star-black-hole binary mergers. There are a number of Python files included in this repository, but the basic workflow is

• generate_nsbh_sample.py: generate sample of simulated mergers (saves parameters and RNG states required to recreate exact noise realisation)
• sim_nsbh_analysis.py: per-merger bilby analysis (use script following hypatia_no_mpi_slurm.sh to accelerate using HPC)
• n_bar_det_farming.py / n_bar_det_processing.py: calculate expected number of detections as function of cosmology (SLURM-able as above)
• population_posteriors.py: optionally fit GW distance likelihoods with Gaussian mixtures, and sample from population and cosmology posteriors

Note the following dependencies:

• AstroPy
• Bilby
• GetDist
• pomegranate
• PyStan
• pypolychord
• scikit-learn

Authors: Stephen Feeney, Hiranya Peiris, Samaya Nissanke and Daniel Mortlock (and Andrew Williamson for ns_eos_aw.py!).