gwGenealogy

gwGenealogy is a Python toolkit for binary black hole (BBH) phenomenology: sampling BBH populations, computing remnant properties, modeling hierarchical mergers in dense star clusters, and analyzing retention across astrophysical environments.

This package is a culmination of my works into understanding hierarchical mergers with my amazing collaborators Digvijay Wadekar and Konstantinos Kritos. Collaborations are always welcome!

Features

  • Distribution samplers — power-law, beta, uniform, Gaussian, log-uniform, Maxwellian, log-normal via gwGenealogy.utils

  • BBH population sampling — masses, spins, redshifts, GWTC-3/4/5 models via gwGenealogy.binaries

  • Remnant properties — mass, spin, and kick velocity for precessing and nonprecessing BBH mergers via BBHRemnant

  • Stellar evolution — Kroupa IMF, Fryer12/SEVN delayed remnant models, natal kicks via gwGenealogy.stellar

  • Host environments — Plummer clusters, escape velocities, environment-marginalised retention via gwGenealogy.hosts

  • Hierarchical mergers — single-cluster (HierarchicalMergersInCluster) and population-averaged (HierarchicalMergersInClusterPopulation) multi-generation merger simulations

  • BH seed growth — Monte Carlo seed growth chains and IMBH formation probability via MonteCarloBHSeedGrowth

  • Retention grids — retention probability heatmaps over the (chi, q) plane via BBHRetentionProbabilityOverChiq