Swarm-intelligent search for gravitational waves from eccentric binary mergers

TL;DR

This paper introduces a particle swarm optimization-based method for detecting gravitational waves from eccentric binary mergers, offering a flexible alternative to traditional template bank searches and demonstrating effectiveness on simulated signals and real candidates.

Contribution

It presents a novel eccentric search algorithm using particle swarm optimization that efficiently explores high-dimensional parameter spaces in gravitational wave detection.

Findings

The search effectively captures eccentricity and spin effects in simulated signals.

It demonstrates comparable or improved detection capabilities over traditional methods.

Revisits and analyzes candidate events from gravitational wave catalogs.

Abstract

We implement an eccentric search for compact binary mergers based on particle swarm optimization. Orbital eccentricity is an invaluable input for understanding the formation scenarios of the binary mergers and can play a pivotal role in finding their electromagnetic counterparts. Current modelled searches rely on pre-computed template banks that are computationally expensive and resistant towards expanding the search parameter space dimensionality. On the other hand, particle swarm optimization offers a straightforward algorithm that dynamically selects template points while exploring an arbitrary dimensional parameter space. Through extensive evaluation using simulated signals from spin-aligned eccentric binary mergers, we discovered that the search exhibits a remarkable autonomy in capturing the effects of both eccentricity and spin. We describe our search pipeline and revisit some of the merger candidates from the gravitational wave transient catalogs.