Mitigating the Counterpart Selection Effect for Standard Sirens.

The disagreement in the Hubble constant measured by different cosmological probes highlights the need for a better understanding of the observations or new physics. The standard siren method, a novel approach using gravitational-wave observations to determine the distance to binary mergers, has great potential to provide an independent measurement of the Hubble constant and shed light on the tension in the next few years. To realize this goal, we must thoroughly understand the sources of potential systematic bias of standard sirens. Among the known sources of systematic uncertainties, selection effects originating from electromagnetic counterpart observations of gravitational-wave sources may dominate the measurements with percent-level bias and no method to mitigate this effect is currently established. In this Letter, we develop a new formalism to mitigate the counterpart selection effect. We show that our formalism can reduce the systematic uncertainty of standard siren Hubble constant measurement to less than the statistical uncertainty with a simulated population of 200 observations (≲1%) for a realistic electromagnetic emission model. We conclude with how to apply our formalism to different electromagnetic emissions and observing scenarios.

Measuring the Primordial Gravitational-Wave Background in the Presence of Astrophysical Foregrounds.

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 multicomponent stochastic background.