Joint Inference of Population, Cosmology, and Neutron Star Equation of State from Gravitational Waves of Dark Binary Neutron Stars
Tathagata Ghosh, Bhaskar Biswas, Sukanta Bose, Shasvath J. Kapadia

TL;DR
This paper introduces a Bayesian method to jointly infer neutron star equation of state, population, and cosmological parameters from gravitational wave data of dark binary neutron star mergers, achieving competitive Hubble constant constraints.
Contribution
The study presents the first Bayesian framework that combines uncertainties in population, cosmology, and neutron star EoS from GW observations of dark BNSs, improving Hubble constant estimation.
Findings
Can constrain Hubble constant with ~35% precision using 50 simulated events.
Method remains effective with as few as 5 events.
Incorporating NS EoS is crucial for accurate cosmological inference.
Abstract
Gravitational waves (GWs) from binary neutron stars (BNSs) are expected to be accompanied by electromagnetic (EM) emissions, which help identify the host galaxy. Since GWs directly measure their luminosity distances, joint GW-EM observations from BNSs help with the study of cosmology, particularly the Hubble constant, unaffected by cosmic distance ladder systematics. However, detecting the EM emissions is not always possible. Additionally, the tidal deformability of neutron stars (NSs), combined with the knowledge of the NS EoS, can break the degeneracy between mass parameters and redshift, allowing for the inference of the Hubble constant. While several studies have aimed to infer the Hubble constant using dark BNSs (without EM counterparts), none have consistently combined the uncertainties of population, cosmology, and NS EoS within a Bayesian framework. In this study, we propose a…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Geophysics and Gravity Measurements · Cosmology and Gravitation Theories
