Reducing the number of templates for aligned-spin compact binary coalescence gravitational wave searches using metric-agnostic template nudging

TL;DR

This paper introduces a template nudging algorithm that reduces the number of templates needed for aligned-spin compact binary coalescence gravitational wave searches by 12%, improving efficiency without sacrificing detection effectiveness.

Contribution

The paper presents a novel, metric-agnostic template nudging method that decreases template count in gravitational wave searches, applicable to various CBC parameter spaces.

Findings

Achieves 12% reduction in template number compared to stochastic methods.

Maintains equivalent effectualness in gravitational wave detection.

Demonstrates generalizability to different CBC parameter spaces.

Abstract

Efficient multi-dimensional template placement is crucial in computationally intensive matched-filtering searches for Gravitational Waves (GWs). Here, we implement the Neighboring Cell Algorithm (NCA) to improve the detection volume of an existing Compact Binary Coalescence (CBC) template bank. This algorithm has already been successfully applied for a binary millisecond pulsar search in data from the Fermi satellite. It repositions templates from over-dense regions to under-dense regions and reduces the number of templates that would have been required by a stochastic method to achieve the same detection volume. Our method is readily generalizable to other CBC parameter spaces. Here we apply this method to the aligned--single-spin neutron-star--black-hole binary coalescence inspiral-merger-ringdown gravitational wave parameter space. We show that the template nudging algorithm can attain the equivalent effectualness of the stochastic method with 12% fewer templates.