Noise Reduction in Gravitational-wave Data via Deep Learning

Understand

With the advent of gravitational wave astronomy, techniques to extend the reach of gravitational wave detectors are desired.

• In addition to the stellar-mass black hole and neutron star mergers already detected, many more are below the surface of the noise, available for detection if the noise is reduced enough.
• Our method (DeepClean) applies machine learning algorithms to gravitational wave detector data and data from on-site sensors monitoring the instrument to reduce the noise in the time-series due to instrumental artifacts and environmental contamination.
• This framework is generic enough to subtract linear, non-linear, and non-stationary coupling mechanisms.