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Full-Text Articles in Instrumentation
Applications Of Machine Learning In Gravitational-Wave Research With Current Interferometric Detectors, Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger
Applications Of Machine Learning In Gravitational-Wave Research With Current Interferometric Detectors, Elena Cuoco, Marco Cavaglià, Ik Siong Heng, David Keitel, Christopher Messenger
Physics Faculty Research & Creative Works
This article provides an overview of the current state of machine learning in gravitational-wave research with interferometric detectors. Such applications are often still in their early days but have reached sufficient popularity to warrant an assessment of their impact across various domains, including detector studies, noise and signal simulations, and the detection and interpretation of astrophysical signals. In detector studies, machine learning could be useful to optimize instruments like LIGO, Virgo, KAGRA, and future detectors. Algorithms could predict and help in mitigating environmental disturbances in real time, ensuring detectors operate at peak performance. Furthermore, machine-learning tools for characterizing and cleaning …
Improving The Background Of Gravitational-Wave Searches For Core Collapse Supernovae: A Machine Learning Approach, M. Cavaglià, S. Gaudio, T. Hansen, K. Staats, M. Szczepanczyk, M. Zanolin
Improving The Background Of Gravitational-Wave Searches For Core Collapse Supernovae: A Machine Learning Approach, M. Cavaglià, S. Gaudio, T. Hansen, K. Staats, M. Szczepanczyk, M. Zanolin
Physics Faculty Research & Creative Works
Based on the priorO1-O2observing runs, about30%of the data collected by Advanced LIGO and Virgo Internext observing runs are expected tobe single-interferometer data, i.e. they will be collected at times when only one detector in the network is operating in observing mode. Searches for gravitational-wave signals from supernova events do not rely on matched filtering techniques because of the stochastic nature of the signals. If a Galactic supernova occurs during single-interferometer times, separation of its unmodelled gravitational-wave signal from noise will be even more difficult due to lack of coherence between detectors. We present a novel machine learning method to perform …