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This thesis presents advancements in the detection of gravitational waves from compact binary coalescences, utilising the most sensitive observatories constructed to date. The research focuses on enhancing gravitational-wave signal searches through the development of new tools and the application of existing methodologies to increase the sensitivity of live gravitational-wave searches. We introduced a novel noise artefact model, which enabled the identification and removal of glitches, thereby facilitating the recovery of previously missed gravitational-wave injections. This pioneering approach established a glitch search pipeline that adapted techniques typically used in gravitational-wave searches to address the unique characteristics of glitches. Additionally, we implemented an exponential noise model within the PyCBC Live search framework, significantly improving the detection ranking statistics for gravitational-wave signals and demonstrating the potential for substantial increases in detection sensitivity. Furthermore, we analysed and proposed enhancements for the PyCBC Live Early Warning search to maximise the detection of gravitational-wave events in the early warning regim

Author

Tolley, Arthur

Published

2025

Language

EN