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Journal Article

Regression of Environmental Noise in LIGO Data

MPS-Authors

Drago,  Marco
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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Salemi,  Francesco
Observational Relativity and Cosmology, AEI-Hannover, MPI for Gravitational Physics, Max Planck Society;

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1503.07476.pdf
(Preprint), 464KB

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Citation

Tiwari, V., Drago, M., Frolov, V., Klimenko, S., Mitselmakher, G., Necula, V., et al. (2015). Regression of Environmental Noise in LIGO Data. Classical and quantum gravity, 32(16): 165014. doi:10.1088/0264-9381/32/16/165014.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0027-9FAA-A
Abstract
We address the problem of noise regression in the output of
gravitational-wave (GW) interferometers, using data from the physical
environmental monitors (PEM). The objective of the regression analysis is to
predict environmental noise in the gravitational-wave channel from the PEM
measurements. One of the most promising regression method is based on the
construction of Wiener-Kolmogorov filters. Using this method, the seismic noise
cancellation from the LIGO GW channel has already been performed. In the
presented approach the Wiener-Kolmogorov method has been extended,
incorporating banks of Wiener filters in the time-frequency domain,
multi-channel analysis and regulation schemes, which greatly enhance the
versatility of the regression analysis. Also we presents the first results on
regression of the bi-coherent noise in the LIGO data.