Seeking Spinning Subpopulations of Black Hole Binaries via Iterative Density Estimation
Jam Sadiq, Thomas Dent, Ana Lorenzo-Medina

TL;DR
This paper develops a minimal-assumption iterative KDE method to analyze black hole binary spin distributions, revealing potential subpopulations and trends that inform their astrophysical origins.
Contribution
It introduces a new iterative kernel density estimation approach to reconstruct BBH parameter distributions with minimal assumptions, uncovering possible high-spin subpopulations and spin-mass trends.
Findings
Identification of a possible high-spin subpopulation with up to |χ_eff| ≈ 0.75 for massive BBHs
Reproduction of known features like positive χ_eff for low-mass mergers
Detection of a new trend in χ_eff derivative with respect to component masses
Abstract
Attempts to understand the formation of binary black hole (BBH) systems detected via gravitational wave (GW) emission are affected by many unknowns and uncertainties, from both the observational and theoretical (astrophysical modelling) sides. Binary component spins have been proposed as a means to investigate formation channels, however obtaining clear inferences is challenging, given the apparently low magnitude of almost all merging BH spins and their high measurement uncertainties. Even for the effective aligned spin which is more precisely measured than component spins, specific model assumptions have been required to identify any clear trends. Here, we reconstruct the joint component mass and distribution of BBH mergers with minimal assumptions using the GWTC-3 catalog, using an iterative kernel density estimation (KDE)-based method. We…
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Taxonomy
TopicsParticle physics theoretical and experimental studies · Black Holes and Theoretical Physics · Quantum Chromodynamics and Particle Interactions
