Noise reduction in gravitational-wave data via deep learning
Rich Ormiston, Tri Nguyên, M. W. Coughlin, R. X. Adhikari, E. Katsavounidis
Abstract
The authors present a method to extend the reach of gravitational wave detectors, which applies machine learning algorithms to the detector data and interprets data from on-site sensors monitoring the instrument to reduce the noise in the time-series due to instrumental artifacts and environmental contamination.
Topics & Concepts
Reduction (mathematics)Gravitational waveNoise (video)Noise reductionData reductionAcousticsComputer sciencePhysicsArtificial intelligenceMathematicsAstronomyData miningGeometryImage (mathematics)Pulsars and Gravitational Waves ResearchSeismic Waves and AnalysisSeismic Imaging and Inversion Techniques