Regression of Environmental Noise in LIGO data

We address the problem of noise regression in the output of gravitational-wave interferometers using data from the environmental monitors (PEM). The objective of the regression analysis is to predict environmental noise in the gravitational-wave (GW) channel from the PEM measurements. One of the most promising regression method is based on the construction of Wiener-Kolmogorov filters. In the presented approach the Wiener-Kolmogorov method has been extended incorporating banks of Wiener filters in the wavelet domain, multi-channel analysis and regulation schemes, which greatly enhance the versatility of the regression analysis. Also we presents the results on regression of the bi-coherent noise in the LIGO data.