Characterizing the observation bias in gravitational-wave detections and finding structured population properties

TL;DR

This paper investigates the bias in gravitational-wave source property distributions caused by detection selection effects, introduces an efficient semi-analytical estimation method, and reveals new population structures such as dual mass peaks.

Contribution

The work provides a fast, accurate semi-analytical approach to estimate observation bias, enabling unmodelled inferences that uncover new features in black hole populations.

Findings

Identification of two mass peaks at ~10 and ~30 solar masses

Development of a computationally efficient bias estimation method

Detection of additional structure in black hole mass distribution

Abstract

The observed distributions of the source properties from gravitational-wave detections are biased due to the selection effects and detection criteria in the detections, analogous to the Malmquist bias. In this work, this observation bias is investigated through its fundamental statistical and physical origins. An efficient semi-analytical formulation for its estimation is derived which is as accurate as the standard method of numerical simulations, with only a millionth of the computational cost. Then, the estimated bias is used for unmodelled inferences on the binary black hole population. These inferences show additional structures, specifically two peaks in the joint mass distribution around binary masses $\sim10$ M$_\odot$ and $\sim30$ M$_\odot$. Example ready-to-use scripts and some produced datasets for this method are shared in an online repository.