Hierarchical Bayesian method for constraining the neutron star equation of state with an ensemble of binary neutron star postmerger remnants

Binary neutron star (BNS) postmerger gravitational-wave emission can occur in the aftermath of a BNS merger - provided the system avoids prompt collapse to a black hole - as a quasistable hypermassive remnant experiences quadrupolar oscillations and nonaxisymmetric deformations. The postmerger gravitational-wave spectrum possesses a characteristic peak frequency that has been shown to be dependent on the binary chirp mass and the neutron star equation of state (EOS), rendering postmerger gravitational waves a powerful tool for constraining neutron star composition. Unfortunately, the BNS postmerger signal is emitted at high (≳1.5 kHz) frequencies, where ground-based gravitational-wave detectors suffer from reduced sensitivity. It is therefore unlikely that postmerger signals will be detected with sufficient signal-to-noise ratio (SNR) until the advent of next-generation detectors. However, by employing empirical relations derived from numerical relativity simulations, we can combine information across an ensemble of BNS mergers, allowing us to obtain EOS constraints with many low-SNR signals. We present a hierarchical Bayesian method for deriving constraints on R1.6, the radius of a 1.6M⊙ neutron star, through an ensemble analysis of binary neutron star mergers. We apply this method to simulations of the next two LIGO-Virgo-KAGRA observing runs, O4 and O5, as well as an extended four-year run at A+ sensitivity, demonstrating the potential of our approach to yield EOS information from the postmerger signal with current-generation detectors. The A+ four-year scenario is predicted to improve the constraint on R1.6 from the currently available multimessenger-based 95% credible interval (C.I.) uncertainty of R1.6=12.07-0.77+0.98 to R1.6=11.91-0.56+0.80 km, a 22% reduction of the 95% C.I. width.