Searches for Post-Merger Gravitational Waves with CoCoA: Sensitivity Projections Across Large Template Banks for Current and Next-Generation Detectors

TL;DR

This paper evaluates the sensitivity of searches for post-merger gravitational waves from neutron star mergers using the CoCoA algorithm across current and future detectors, aiding in optimizing search strategies.

Contribution

It introduces a Python framework to estimate CoCoA detection horizons for various post-merger waveforms and detector networks, enhancing search planning.

Findings

Framework estimates detection horizons for post-merger signals.

Identifies promising parameter space regions for future searches.

Supports optimizing search sensitivity versus computational cost.

Abstract

The multi-messenger detection of the binary neutron star (NS) merger GW170817 has revolutionized the field of gravitational wave (GW) astronomy. However, several important questions remain to be answered. One of these is the nature of the compact remnant leftover by GW170817 (short- or long-lived NS versus black hole). A key goal going forward is to understand the diversity of NS-NS merger remnants, and how such diversity maps onto their viability as gamma-ray burst (GRB) central engines. Here, we present a study aimed at assessing the sensitivity of triggered searches for intermediate-duration, post-merger GWs powered by long-lived GRB remnants using networks of current and future ground-based GW detectors and the Cross-Correlation Algorithm (CoCoA). We develop a Python-based framework to efficiently estimate CoCoA distance horizons for a broad range of post merger secular bar-mode waveforms and for different GW detector networks. This framework can be used to identify the most promising regions of parameter space in which to concentrate search efforts, helping design future search strategies to optimally balance search sensitivity and related parameter space gridding schema against computational cost.