Data Release for "Avoiding a Cluster Catastrophe: Retention Efficiency and the Binary Black Hole Mass Spectrum"

Data release associated with "Avoiding a Cluster Catastrophe: Retention Efficiency and the Binary Black Hole Mass Spectrum"(arxiv: 2205.08549). 

This contains all data used in the paper, as well as a Jupyter notebook that reproduces all figures in the paper. 

• The three tarballs (`Tdel_10_100.tar.gz`, `Tdel_10_1000.tar.gz`, and `Tdel_100_14000.tar.gz`) contain multiple realizations for each time delay model explored. These just need to be unzipped and are combined in the supplied notebook. These are read in as Pandas dataframes and contain information about merger trees, such as properties of the components of the merger (masses, spins, redshifts), the merger product (remnant spin, remnant mass, recoil kick velocity), and a number of Booleans that determine whether a given merger is possible when constrained by either host environment escape velocity or black hole budget. 
• `posterior_predictive.hdf5` contains pre-drawn systems from the Power Law + Peak model of GWTC-3; these are by default read in by the script so that the user does not need to redraw these systems each time. 
• `hierarchical_mergers_clean.ipynb` is a Jupyter notebook that generates all the figures in the paper using the other data products from this release.