Estimation of the Hubble parameter from unedited compact object merger catalogues

Abstract In recent years, constraints on the Hubble parameter using multiple dark sirens have been made, relying on a galaxy catalogue, correlations between the mass and redshift distributions, or both. Those studies have typically used only significant gravitational wave candidates. In this work, we present a framework for cosmological inference that bypasses per-candidate parameter estimation, uses only detection-level information. This allows the population inference from a candidate list produced directly by a search pipeline, without additional selection cuts. Our method is particularly suited to extracting information from marginal candidates, which are essential for probing the distant Universe. The goal of this work is not to present a constraint of the Hubble constant at this time, our primary goal is to explain the framework. To this end we present worked examples of the application of the technique to synthetic data to exhibit its performance and the novel challenges it brings.