Long gravitational-wave transients and associated detection strategies for a network of terrestrial interferometers

TL;DR

This paper introduces a new method for detecting long-duration gravitational-wave transients with unknown waveforms using frequency-time maps and pattern recognition, bridging the gap between short burst and persistent source analyses.

Contribution

It proposes a novel analysis technique based on frequency-time maps and pattern recognition to detect long GW transients, addressing a previously unexplored timescale range.

Findings

Successfully recovered simulated GW signals in noise

Identified environmental noise artifacts effectively

Compared favorably to matched filtering techniques

Abstract

Searches for gravitational waves (GWs) traditionally focus on persistent sources (e.g., pulsars or the stochastic background) or on transients sources (e.g., compact binary inspirals or core-collapse supernovae), which last for timescales of milliseconds to seconds. We explore the possibility of long GW transients with unknown waveforms lasting from many seconds to weeks. We propose a novel analysis technique to bridge the gap between short O(s) burst analyses and persistent stochastic analyses. Our technique utilizes frequency-time maps of GW strain cross-power between two spatially separated terrestrial GW detectors. The application of our cross-power statistic to searches for GW transients is framed as a pattern recognition problem, and we discuss several pattern-recognition techniques. We demonstrate these techniques by recovering simulated GW signals in simulated detector noise. We also recover environmental noise artifacts, thereby demonstrating a novel technique for the identification of such artifacts in GW interferometers. We compare the efficiency of this framework to other techniques such as matched filtering.