Machine-learning nonstationary noise out of gravitational-wave detectors

Machine-learning nonstationary noise out of gravitational-wave detectors

Signal extraction out of background noise is a common challenge in high-precision physics experiments, where the measurement output is often a continuous data stream. To improve the signal-to-noise ratio of the detection, witness sensors are often used to independently measure background noises and...

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Bibliographic Details
Main Authors: Vajente, G., Huang, Yiwen, Isi Banales, Maximiliano S, Driggers, J. C., Kissel, J. S., Szczepańczyk, M. J., Vitale, Salvatore
Other Authors: MIT Kavli Institute for Astrophysics and Space Research
Format: Article
Language:English
Published: American Physical Society 2020
Online Access:https://hdl.handle.net/1721.1/124384

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https://hdl.handle.net/1721.1/124384

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