Parameterised population models of transient non-Gaussian noise in the LIGO gravitational-wave detectors

TL;DR

This paper develops parameterized models of transient non-Gaussian noise in LIGO data, comparing their properties with astrophysical signals to improve noise mitigation and candidate validation in gravitational-wave detection.

Contribution

It introduces a novel method to model transient noise populations in parameter space and assess candidate consistency with noise classes, enhancing detection reliability.

Findings

Transient noise artefacts have extreme mass ratios and large spins.

Astrophysical signals tend to have near-equal masses and moderate spins.

The method can improve candidate validation and detector sensitivity.

Abstract

The two interferometric LIGO gravitational-wave observatories provide the most sensitive data to date to study the gravitational-wave Universe. As part of a global network, they have just completed their third observing run in which they observed many tens of signals from merging compact binary systems. It has long been known that a limiting factor in identifying transient gravitational-wave signals is the presence of transient non-Gaussian noise, which reduce the ability of astrophysical searches to detect signals confidently. Significant efforts are taken to identify and mitigate this noise at the source, but its presence persists, leading to the need for software solutions. Taking a set of transient noise artefacts categorised by the GravitySpy software during the O3a observing era, we produce parameterised population models of the noise projected into the space of astrophysical model parameters of merging binary systems. We compare the inferred population properties of transient noise artefacts with observed astrophysical systems from the GWTC2.1 catalogue. We find that while the population of astrophysical systems tend to have near equal masses and moderate spins, transient noise artefacts are typically characterised by extreme mass ratios and large spins. This work provides a new method to calculate the consistency of an observed candidate with a given class of noise artefacts. This approach could be used in assessing the consistency of candidates found by astrophysical searches (i.e. determining if they are consistent with a known glitch class). Furthermore, the approach could be incorporated into astrophysical searches directly, potentially improving the reach of the detectors, though only a detailed study would verify this.