# Accelerated detection of the binary neutron star gravitational-wave background

## TL;DR

This paper presents a Bayesian method to detect the gravitational-wave background from binary neutron star mergers, significantly reducing the observation time needed compared to traditional techniques.

## Contribution

It introduces a Bayesian parameter estimation approach for extracting sub-threshold signals, enabling faster detection and differentiation of neutron star equations of state.

## Key findings

- Detection possible after three months of data at design sensitivity
- Method distinguishes neutron star equations of state within seven months
- Reduces detection time from years to months

## Abstract

Most gravitational-wave signals from binary neutron star coalescences are too weak to be individually resolved with current detectors. We demonstrate how to extract a population of sub-threshold binary neutron star signals using Bayesian parameter estimation. Assuming a merger rate of one signal every two hours, we find that this gravitational-wave background can be detected after approximately three months of observation with Advanced LIGO and Virgo at design sensitivity, versus several years using the standard cross-correlation algorithm. We show that the algorithm can distinguish different neutron star equations of state using roughly seven months of Advanced LIGO and Virgo design-sensitivity data. This is in contrast to the standard cross-correlation method, which cannot.