Multiresolution techniques for the detection of gravitational-wave bursts

TL;DR

This paper introduces two novel multiresolution algorithms for detecting unmodeled gravitational-wave bursts, utilizing wavelet and Fourier transforms, along with adaptive whitening, to improve detection efficiency in noisy data.

Contribution

It presents new multiresolution detection algorithms and preprocessing techniques for gravitational-wave burst identification, with initial validation on simulated LIGO noise.

Findings

Effective detection of gravitational-wave bursts demonstrated

Adaptive whitening simplifies statistical analysis

Algorithms show promising preliminary performance

Abstract

We present two search algorithms that implement logarithmic tiling of the time-frequency plane in order to efficiently detect astrophysically unmodeled bursts of gravitational radiation. The first is a straightforward application of the dyadic wavelet transform. The second is a modification of the windowed Fourier transform which tiles the time-frequency plane for a specific Q. In addition, we also demonstrate adaptive whitening by linear prediction, which greatly simplifies our statistical analysis. This is a methodology paper that aims to describe the techniques for identifying significant events as well as the necessary pre-processing that is required in order to improve their performance. For this reason we use simulated LIGO noise in order to illustrate the methods and to present their preliminary performance.