Speaker
Description
The observation of gravitational waves (GWs) from dark sirens provides a novel measurement, complementary to other surveys that are electromagnetic (EM) signal–based. Under the assumption that both observations trace the distribution of matter up to some bias parameters, it is possible to infer cosmological parameters by cross-correlating their density maps.
As the number of resolved GW sources is growing with rapidly advancing technologies, we estimate the population of dark sirens that will be detected by future observations such as LIGO-Virgo-Kagra, the Einstein Telescope and the Cosmic Explorer. We compute the cross-correlation between dark sirens' mock data and other surveys from EM observations, such as galaxy clustering or the Integrated Sachs-Wolfe (ISW) effect. We fit the cross-correlation angular power spectrum by running Markov Chain Monte Carlo (MCMC) with an innovative likelihood. Our results demonstrate the potential of this method to provide new and independent constraints on cosmological parameters such as the Hubble constant, while also revealing the informative contribution of cross-correlations between a range of observables.
