Machine Learning to Optimize Newtonian Noise Cancellation in Third-Generation Gravitational Wave Detectors
摘要
Newtonian noise affects gravitational wave detectors in the low frequency band (below 20 Hz). It is generated by gravity fluctuations happening nearby the detector. Being it related to passing seismic waves, it can be predicted by monitoring the seismic field. The Einstein Telescope, a third-generation gravitational-wave detector, will be built underground and it will need a Newtonian noise cancellation system. In this paper we discuss how a cancellation system can be designed when the available seismic data will be scarce.