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Full-Text Articles in Astrophysics and Astronomy
Nnetfix: An Artificial Neural Network-Based Denoising Engine For Gravitational-Wave Signals, Kentaro Mogushi, Ryan Quitzow-James, Marco Cavaglià, Sumeet Kulkarni, Fergus Hayes
Nnetfix: An Artificial Neural Network-Based Denoising Engine For Gravitational-Wave Signals, Kentaro Mogushi, Ryan Quitzow-James, Marco Cavaglià, Sumeet Kulkarni, Fergus Hayes
Faculty and Student Publications
Instrumental and environmental transient noise bursts in gravitational-wave (GW) detectors, or glitches, may impair astrophysical observations by adversely affecting the sky localization and the parameter estimation of GW signals. Denoising of detector data is especially relevant during low-latency operations because electromagnetic follow-up of candidate detections requires accurate, rapid sky localization and inference of astrophysical sources. NNETFIX is a machine learning, artificial neural network-based algorithm designed to estimate the data containing a transient GW signal with an overlapping glitch as though the glitch was absent. The sky localization calculated from the denoised data may be significantly more accurate than the sky …