Which is which? Identification of the two compact objects in gravitational-wave binaries

TL;DR

This paper introduces a new method using constrained clustering to improve the identification of binary components in gravitational-wave data, enhancing parameter estimation and object classification accuracy.

Contribution

It proposes a novel approach to object labeling in gravitational-wave analysis, moving beyond mass-based labels to a clustering-based method that reduces systematics and improves parameter inference.

Findings

Black-hole spin measurement precision improves by up to 50%.

Posteriors become more Gaussian and less multimodal.

Approximately 10% of LIGO/Virgo samples are affected by relabeling.

Abstract

Compact objects observed in gravitational-wave astronomy so far always come in pairs and never individually. Identifying the two components of a binary system is a delicate operation that is often taken for granted. The labeling procedure (i.e., which is object "1" and which is object "2") effectively acts as systematics, or, equivalently an unspecified prior, in gravitational-wave data inference. The common approach is to label the objects solely by their masses, on a sample-by-sample basis. We show that object identification can instead be tackled using the posterior distribution as a whole. We frame the problem in terms of constrained clustering -- a flavor of semi-supervised machine learning -- and find that unfolding the labeling systematics can significantly impact, and arguably improve, our interpretation of the data. In particular, the precision of black-hole spin measurements improves by up to 50%, multimodalities and tails tend to disappear, posteriors become closer to Gaussian distributions, and the identification of the nature of the object (i.e. black hole vs. neutron star) is facilitated. We estimate that about 10% of the LIGO/Virgo posterior samples are affected by this relabeling, i.e. they might have been attributed to the other compact object in the observed binaries.