A stochastic search for intermittent gravitational-wave backgrounds

TL;DR

This paper introduces a new stochastic search method tailored for detecting intermittent gravitational-wave backgrounds, which are better modeled by Gaussian mixture models due to their popcorn-like nature, improving detection over traditional continuous models.

Contribution

The paper develops a stochastic-signal-based search method for intermittent GWBs using Gaussian mixture models, outperforming standard continuous cross-correlation searches in simulated data.

Findings

The new method shows improved detection capabilities for intermittent GWBs.

Simulation results demonstrate better signal characterization with the proposed approach.

Further testing on realistic data is needed for real-world application.

Abstract

A likely source of a gravitational-wave background (GWB) in the frequency band of the Advanced LIGO, Virgo and KAGRA detectors is the superposition of signals from the population of unresolvable stellar-mass binary-black-hole (BBH) mergers throughout the Universe. Since the duration of a BBH merger in band ($\sim\!1~{\rm s}$) is much shorter than the expected separation between neighboring mergers ($\sim\!10^3~{\rm s}$), the observed signal will be "popcorn-like" or intermittent with duty cycles of order $10^{-3}$. However, the standard cross-correlation search for stochastic GWBs currently performed by the LIGO-Virgo-KAGRA collaboration is based on a continuous-Gaussian signal model, which does not take into account the intermittent nature of the background. The latter is better described by a Gaussian mixture-model, which includes a duty cycle parameter that quantifies the degree of intermittence. Building on an earlier paper by Drasco and Flanagan, we propose a stochastic-signal-based search for intermittent GWBs. For such signals, this search performs better than the standard continuous cross-correlation search. We present results of our stochastic-signal-based approach for intermittent GWBs applied to simulated data for some simple models, and compare its performance to the other search methods, both in terms of detection and signal characterization. Additional testing on more realistic simulated data sets, e.g., consisting of astrophysically-motivated BBH merger signals injected into colored detector noise containing noise transients, will be needed before this method can be applied with confidence on real gravitational-wave data.