An efficient filter for detecting gravitational wave bursts in interferometric detectors

TL;DR

This paper introduces the ALF filter, a highly efficient and robust method for detecting gravitational wave bursts from sources like supernovae, suitable for real-time data analysis in interferometric detectors.

Contribution

The paper presents a novel non-linear filter called ALF, based on linear fits to whitened data, which outperforms other filters in detecting supernova burst signals.

Findings

ALF achieves about 80% of the optimal filter performance.

ALF is the most efficient among tested filters.

Potential for real-time implementation in gravitational wave detectors.

Abstract

Typical sources of gravitational wave bursts are supernovae, for which no accurate models exist. This calls for search methods with high efficiency and robustness to be used in the data analysis of foreseen interferometric detectors. A set of such filters is designed to detect gravitational wave burst signals. We first present filters based on the linear fit of whitened data to short straight lines in a given time window and combine them in a non linear filter named ALF. We study the performances and efficiencies of these filters, with the help of a catalogue of simulated supernova signals. The ALF filter is the most performant and most efficient of all filters. Its performance reaches about 80% of the Optimal Filter performance designed for the same signals. Such a filter could be implemented as an online trigger (dedicated to detect bursts of unknown waveform) in interferometric detectors of gravitational waves.