Nonparametric analysis of correlations in the binary black hole population with LIGO-Virgo-KAGRA data

Kavli Affiliate: Salvatore Vitale

| First 5 Authors: Jack Heinzel, Matthew Mould, Salvatore Vitale, ,

| Summary:

Formation channels of merging compact binaries imprint themselves on the
distributions and correlations of their source parameters, but current
understanding of this population is hindered by simplified parametric models.
We overcome such limitations using PixelPop [Heinzel et al. (2024)]-our
Bayesian nonparametric multidimensional population model. We analyze data from
the first three LIGO-Virgo-KAGRA observing runs and make high resolution,
minimally modeled measurements of the pairwise distributions of binary black
hole masses, redshifts, and spins. We find no evidence that the mass spectrum
evolves over redshift and show that such measurements are fundamentally limited
by the detector horizon. We find support for correlations of the spin
distribution with binary mass ratio and redshift, but at reduced significance
compared to overly constraining parametric models. Confident data-driven
conclusions about population-level correlations with flexible models like
PixelPop will require more informative gravitational-wave catalogs.

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