Interferometric gravitational-wave observatories have opened a new era in astronomy. The rich data produced by an international network enable detailed analysis of the curved space-time around black holes. With nearly 100 signals observed so far and thousands expected in the next decade, their population properties enable insights into stellar evolution and the expansion of our Universe. However, the detectors are afflicted by transient noise artefacts known as ‘glitches’ which contaminate the signals and bias inferences. Of the 90 signals detected to date, 18 were contaminated by glitches. This feasibility study explores a new approach to transient gravitational-wave data analysis using Gaussian processes, which model the underlying physics of the glitch-generating mechanism rather than the explicit realization of the glitch itself. We demonstrate that if the Gaussian process kernel function can adequately model the glitch morphology, we can recover the parameters of simulated signals. Moreover, we find that the Gaussian processes kernels used in this work are well suited to modelling long-duration glitches which are most challenging for existing glitch-mitigation approaches. Finally, we show how the time-domain nature of our approach enables a new class of time-domain tests of General Relativity, performing a re-analysis of the inspiral-merger-ringdown test on the first observed binary black hole merger. Our investigation demonstrates the feasibility of the Gaussian processes as an alternative to the traditional framework but does not yet establish them as a replacement. Therefore, we conclude with an outlook on the steps needed to realize the full potential of the Gaussian process approach.
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 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.
more » « less- NSF-PAR ID:
- 10369729
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Classical and Quantum Gravity
- Volume:
- 39
- Issue:
- 17
- ISSN:
- 0264-9381
- Page Range / eLocation ID:
- Article No. 175004
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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