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.utilsBBH population sampling — masses, spins, redshifts, GWTC-3/4/5 models via
gwGenealogy.binariesRemnant properties — mass, spin, and kick velocity for precessing and nonprecessing BBH mergers via
BBHRemnantStellar evolution — Kroupa IMF, Fryer12/SEVN delayed remnant models, natal kicks via
gwGenealogy.stellarHost environments — Plummer clusters, escape velocities, environment-marginalised retention via
gwGenealogy.hostsHierarchical mergers — single-cluster (
HierarchicalMergersInCluster) and population-averaged (HierarchicalMergersInClusterPopulation) multi-generation merger simulationsBH seed growth — Monte Carlo seed growth chains and IMBH formation probability via
MonteCarloBHSeedGrowthRetention grids — retention probability heatmaps over the (chi, q) plane via
BBHRetentionProbabilityOverChiq
Contents
- Installation
- Quick Start
- API Reference
- Tutorials
- Core Distribution Samplers
- Stellar Evolution and 1G BH Masses
- BBH Remnants: Nonprecessing Models
- BBH Remnants: Precessing Models
- GWTC Population Sampling
- Retention Probability Over the (chi, q) Plane
- Host Environments and Retention
- Hierarchical BH Mergers in Dense Star Clusters
- BH Seed Growth Demo
- Remnant Displacement and Return Times
- Hierarchical BH Mergers in a Single Star Cluster
- Inferring the progenitor of a recoiling SMBH: JWST RBH-1
- Citation