Detecting Binary Compact-object Mergers with Gravitational Waves: Understanding and Improving the Sensitivity of the PyCBC Search

Abstract

We present an improved search for binary compact-object mergers using a network of ground-based gravitational-wave detectors. We model a volumetric, isotropic source population and incorporate the resulting distribution over signal amplitude, time delay, and coalescence phase into the ranking of candidate events. We describe an improved modeling of the background distribution, and demonstrate incorporating a prior model of the binary mass distribution in the ranking of candidate events. We find an ∼ 10 % and ∼ 20 % increase in detection volume for simulated binary neutron star and neutron star black hole systems, respectively, corresponding to a reduction of the false alarm rates assigned to signals by between one and two orders of magnitude.