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Journal Article

Application of the independent component analysis to the iKAGRA data


Shibata,  M.
Computational Relativistic Astrophysics, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

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KAGRA Collaboration, Akutsu, T., Ando, M., Arai, K., Arai, Y., Araki, S., et al. (2020). Application of the independent component analysis to the iKAGRA data. Progress of Theoretical and Experimental Physics, 2020(5): 053F01. doi:10.1093/ptep/ptaa056.

Cite as: https://hdl.handle.net/21.11116/0000-0004-CCA1-0
We apply independent component analysis (ICA) to the real data from a
gravitational wave detector for the first time. ICA separates various sources
of signals from multiple detection channels making use of non-Gaussian nature
of the statistical distributions of the sources. Specifically we use the iKAGRA
data taken in April 2016, and calculate the correlations between the
gravitational wave strain channel and 35 physical environmental channels. Using
a couple of seismic channels which are found to be strongly correlated with the
strain, we perform ICA. Injecting a sinusoidal continuous signal in the strain
channel, we find that ICA recovers correct parameters with enhanced
signal-to-noise ratio, which demonstrates usefulness of this method.