Measuring the primordial gravitational-wave background in the presence of astrophysical foregrounds

TL;DR

This paper introduces a Bayesian method to accurately estimate primordial gravitational-wave backgrounds by simultaneously modeling and accounting for astrophysical foregrounds, avoiding contamination and residual errors.

Contribution

The paper presents a novel Bayesian framework that jointly estimates primordial and astrophysical gravitational-wave signals, incorporating non-Gaussianity for optimal detection.

Findings

Effective separation of primordial and astrophysical signals

Avoidance of residual contamination in measurements

Statistically optimal detection approach

Abstract

Primordial gravitational waves are expected to create a stochastic background encoding information about the early Universe that may not be accessible by other means. However, the primordial background is obscured by an astrophysical foreground consisting of gravitational waves from compact binaries. We demonstrate a Bayesian method for estimating the primordial background in the presence of an astrophysical foreground. Since the background and foreground signal parameters are estimated simultaneously, there is no subtraction step, and therefore we avoid astrophysical contamination of the primordial measurement, sometimes referred to as "residuals". Additionally, since we include the non-Gaussianity of the astrophysical foreground in our model, this method represents the statistically optimal approach to the simultaneous detection of a multi-component stochastic background.