Work

Particle swarm optimization based search for gravitational waves from compact binary coalescences: Performance improvements

Year: 2018

Type: article

Abstract: While a fully coherent all-sky search is known to be optimal for detecting signals from compact binary coalescences (CBCs), its high computational cost has limited current searches to less sensitive coincidence-based schemes. For a network of first-generation GW detectors, it has been demonstrated that particle swarm optimization (PSO) can reduce the computational cost of this search, in terms of the number of likelihood evaluations, by a factor of $\ensuremath{\approx}10$ compared to a grid-based optimizer. Here, we extend the PSO-based search to a network of second-generation detectors and present further substantial improvements in its performance by adopting the local-best variant of PSO and an effective strategy for tuning its configuration parameters. It is shown that a PSO-based search is viable over the entire binary mass range relevant to second-generation detectors at realistic signal strengths.

Source: Physical review. D/Physical review. D.

DOI: 10.1103/physrevd.98.044029

Authors: Marc E. Normandin, Soumya D. Mohanty, Thilina S. Weerathunga

Institution: The University of Texas at San Antonio

Language: English

Topic: Pulsars and Gravitational Waves Research

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, University of Texas at Austin

Awards: Support of LIGO Data Analysis Activities at the University of Texas at Brownsville, Expanding interdisciplinary research at the Center for Gravitational Wave Astronomy, MRI: Acquisition of a PC Cluster, High Performance Pan American Cluster (HiPAC)