Exploration of features in the black hole mass spectrum inspired by non-parametric analyses of gravitational wave observations

TL;DR

This paper compares non-parametric and parametric models to analyze gravitational wave data, revealing potential subpopulations in black hole masses and highlighting current limitations in understanding mass ratio distributions.

Contribution

It introduces two modified PowerLaw+Peak models inspired by non-parametric analyses and applies them to gravitational wave data, bridging different modeling approaches.

Findings

Evidence for two distinct black hole subpopulations.

Current data insufficient to determine mass ratio distribution shape.

Models support the existence of redshift-evolving mass features.

Abstract

Current gravitational-wave data reveal structures in the mass function of binary compact objects. Properly modelling and deciphering such structures is the ultimate goal of gravitational-wave population analysis: in this context, non-parametric models are a powerful tool to infer the distribution of black holes from gravitational waves without committing to any specific functional form. Here, we aim to quantitatively corroborate the findings of non-parametric methods with parametrised models incorporating the features found in such analyses. We propose two modifications of the currently favoured PowerLaw+Peak model, inspired by non-parametric studies, and use them to analyse the third Gravitational Wave Transient Catalogue. Our analysis marginally supports the existence of two distinct, differently redshift-evolving subpopulations in the black hole primary mass function, and suggests that, to date, we are still unable to robustly assess the shape of the mass ratio distribution for symmetric ($q>0.7$) binaries.