# Detecting binary compact-object mergers with gravitational waves: Understanding and Improving the sensitivity of the PyCBC search

## TL;DR

This paper enhances gravitational wave searches for binary mergers by modeling source populations and background distributions, leading to significant improvements in detection volume and false alarm rate reduction.

## Contribution

It introduces a new method that incorporates source population models and background distribution improvements into the detection ranking process.

## Key findings

- Approximately 10% increase in detection volume for binary neutron stars.
- Approximately 20% increase in detection volume for neutron star-black hole systems.
- False alarm rates reduced by one to two orders of magnitude.

## 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 a $\sim 10\%$ and $\sim 20\%$ increase in detection volume for simulated binary neutron star and neutron star--binary black hole systems, respectively, corresponding to a reduction of the false alarm rates assigned to signals by between one and two orders of magnitude.