Toward the detection of gravitational waves under non-Gaussian noises II. Independent Component Analysis

TL;DR

This paper presents a novel independent component analysis approach to improve gravitational wave detection by effectively separating signals from non-Gaussian noise sources, including linear, delayed, and nonlinear noise couplings.

Contribution

It introduces an advanced ICA-based method capable of handling complex non-Gaussian noise structures in gravitational wave data analysis.

Findings

Enhanced signal-to-noise ratio in simulated data

Successful identification of coupling coefficients in nonlinear noise models

Applicable to general signal detection under non-Gaussian noise conditions

Abstract

We introduce a new analysis method to deal with stationary non-Gaussian noises in gravitational wave detectors in terms of the independent component analysis. First, we consider the simplest case where the detector outputs are linear combinations of the inputs, consisting of signals and various noises, and show that this method may be helpful to increase the signal-to-noise ratio. Next, we take into account the time delay between the inputs and the outputs. Finally, we extend our method to nonlinearly correlated noises and show that our method can identify the coupling coefficients and remove non-Gaussian noises. Although we focus on gravitational wave data analysis, our methods are applicable to the detection of any signals under non-Gaussian noises.