Spectrogram correlated stacking: A novel time-frequency domain analysis of the Stochastic Gravitational Wave Background

TL;DR

This paper introduces Spectrogram Correlated Stacking (SpeCs), a new time-frequency domain analysis technique that enhances the detection of the stochastic gravitational wave background by exploiting higher-order statistics, significantly improving sensitivity over traditional methods.

Contribution

The paper presents SpeCs, a novel method that surpasses standard cross-correlation by utilizing higher-order time-frequency statistics to detect the SGWB more effectively.

Findings

SpeCs improves signal-to-noise ratio by nearly 8 times.

It can probe beyond the power spectrum of the SGWB.

Application to GW data accelerates SGWB discovery.

Abstract

The astrophysical stochastic gravitational wave background (SGWB) originates from numerous faint sub-threshold gravitational wave (GW) signals arising from the coalescing binary compact objects. This background is expected to be discovered from the current (or next-generation) network of GW detectors by cross-correlating the signal between multiple pairs of GW detectors. However, detecting this signal is challenging and the correlation is only detectable at low frequencies due to the arrival time delay between different detectors. In this work, we propose a novel technique, \texttt{Spectrogram Correlated Stacking} (or \texttt{SpeCs}), which goes beyond the usual cross-correlation (and to higher frequencies) by exploiting the higher-order statistics in the time-frequency domain which accounts for the \textit{chirping} nature of the individual events that comprise SGWB. We show that \texttt{SpeCs} improves the signal-to-noise for the detection of SGWB by a factor close to $8$, compared to standard optimal cross-correlation methods which are tuned to measure only the power spectrum of the SGWB signal.\texttt{SpeCs} can probe beyond the power spectrum and its application to the GW data available from the current and next-generation GW detectors would speed up the SGWB discovery.