Wavelet entropy filter and cross-correlation of gravitational wave data

TL;DR

This paper introduces a wavelet entropy filter to enhance the detection of gravitational wave signals by optimizing time-frequency resolution and suppressing noise through wavelet decomposition and entropy-based selection.

Contribution

The method applies wavelet entropy filtering to improve cross-correlation of gravitational wave signals in noisy data streams, enhancing signal detection capabilities.

Findings

Effective in increasing signal-to-noise ratio

Improves detection of weak gravitational wave signals

Applicable to uncorrelated noise environments

Abstract

We present a method for enhancing the cross-correlation of gravitational wave signals eventually present in data streams containing otherwise uncorrelated noise. Such method makes use of the wavelet decomposition to cast the cross-correlation time series in time-frequency space. Then an entropy criterion is applied to identify the best time frequency resolution, i.e. the resolution allowing to concentrate the signal in the smallest number of wavelet coefficients. By keeping only the coefficients above a certain threshold, it is possible to reconstruct a cross-correlation time series where the effect of common signal is stronger. We tested our method against signals injected over two data streams of uncorrelated white noise.