Inferring the pair-instability mass gap from gravitational wave data

TL;DR

This paper uses hierarchical Bayesian inference to analyze gravitational wave data, revealing a mass gap in black hole populations and suggesting the presence of second-generation black holes formed from previous mergers.

Contribution

It introduces a non-parametric Gaussian process approach to study the effective spin parameter as a function of black hole mass, providing model-independent evidence for the pair-instability mass gap.

Findings

Identifies a transition in black hole spin distribution at ~46 solar masses.

Finds the spin distribution broadens and becomes symmetric above the mass gap.

Constrains the fraction of second-generation black holes to be less than 10%.

Abstract

We use hierarchical Bayesian inference with non-parametric Gaussian process models to investigate the effective inspiral spin parameter, $\chi_{\rm eff}$, as a function of primary black hole mass in the third gravitational-wave transient catalog (GWTC-3). Our analysis reveals a transition in the population at a primary mass of $46^{+7}_{-5}\,M_\odot$. Beyond this mass, the $\chi_{\rm eff}$ distribution broadens, becomes consistent with being symmetric around zero, and has a median of $-0.03^{+0.36}_{-0.59}$ (90\% credibility). These results are consistent with the presence of a pair-instability mass gap that is repopulated by black holes that are the remnant of a previous merger, formed in dense star clusters. However, asymmetric distributions skewed toward positive $\chi_{\rm eff}$ are not excluded by current data. Below the inferred transition mass, we constrain the fraction of second-generation black holes to be $\lesssim 10\%$. These results provide model-independent support for a high-mass and high-spin population of black holes in the data, consistent with earlier work using parametric models. Imminent gravitational-wave data releases will be essential to sharpen constraints on spin symmetry and clarify the origin of the black holes.