Analyzing intermittent stochastic gravitational wave background I:Effect of detector response

TL;DR

This paper improves detection strategies for non-Gaussian gravitational-wave backgrounds by accounting for detector response anisotropies, reducing biases in parameter estimation, and maintaining robustness for anisotropic sources.

Contribution

It introduces a method that incorporates second-order corrections to account for detector response anisotropies, enhancing the accuracy of non-Gaussian background detection.

Findings

Properly modeling detector response reduces biases in parameter estimation.

The proposed method effectively accounts for anisotropic backgrounds.

Incorporating second-order corrections improves detection robustness.

Abstract

With the growing number of gravitational-wave detections, particularly from binary black hole mergers, there is increasing anticipation that an astrophysical background, formed by an ensemble of faint, high-redshift events, will be observed in the near future by the ground-based detector network. This background is anticipated to exhibit non-Gaussian statistical properties. To develop a robust method for detecting such a non-Gaussian gravitational-wave background, we revisit optimal detection strategies based on the Gaussian-mixture likelihood model. In this work, we demonstrate that properly accounting for the detector antenna pattern is essential. Current approaches typically rely on the overlap reduction function averaged over the sky. Through simulations, we show that using such an averaged response introduces significant biases in parameter estimation. In addition, we propose a computationally feasible method that incorporates second-order corrections as an approximation of the full integral over the source distribution. Our results indicate that this approach effectively eliminates these biases. We also show that our method remains robust even when considering anisotropic backgrounds.