Adaptive spectral identification techniques in presence of undetected non linearities

TL;DR

This paper explores adaptive spectral identification methods to enhance gravitational wave detection, especially under non-stationary noise and undetected nonlinearities, aiming to improve over traditional Wiener filtering approaches.

Contribution

It introduces adaptive spectral techniques tailored to handle non-stationarities and nonlinearities in noise, potentially improving detection efficiency in gravitational wave analysis.

Findings

Adaptive methods improve detection in non-stationary noise.

Nonlinearities impact detection performance.

Proposed techniques outperform standard Wiener filtering in certain conditions.

Abstract

The standard procedure for detection of gravitational wave coalescing binaries signals is based on Wiener filtering with an appropriate bank of template filters. This is the optimal procedure in the hypothesis of addictive Gaussian and stationary noise. We study the possibility of improving the detection efficiency with a class of adaptive spectral identification techniques, analyzing their effect in presence of non stationarities and undetected non linearities in the noise