Uncertainty and Bias of Cosmology and Astrophysical Population Model from Statistical Dark Sirens

Abstract

Gravitational-wave (GW) radiation from a coalescing compact binary is a standard siren, as the luminosity distance of each event can be directly measured from the amplitude of the signal. One possibility to constrain cosmology using the GW siren is to perform statistical inference on a population of binary black hole (BBH) events. In essence, this statistical method can be viewed as follows. We can modify the shape of the distribution of observed BBH events by changing the cosmological parameters until it eventually matches the distribution constructed from an astrophysical population model, thereby allowing us to determine the cosmological parameters. In this work, we derive the Cramér–Rao bound for both cosmological parameters and those governing the astrophysical population model from this statistical dark siren method by examining the Fisher information contained in the event distribution. Our study provides analytical insights and enables fast yet accurate estimations of the statistical accuracy of dark siren cosmology. Furthermore, we consider the bias in cosmology due to unmodeled substructures in the merger rate and mass distribution. We find that a 1% deviation in the astrophysical model can lead to a more than 1% error in the Hubble constant. This could limit the accuracy of dark siren cosmology when there are more than 104 BBH events detected.