Zou, X.-B.; Mohanty, S.D.; Luo, H.-G.; Liu, Y.-X. Swarm Intelligence Methods for Extreme Mass Ratio Inspiral Search: First Application of Particle Swarm Optimization. Universe2024, 10, 96.
Zou, X.-B.; Mohanty, S.D.; Luo, H.-G.; Liu, Y.-X. Swarm Intelligence Methods for Extreme Mass Ratio Inspiral Search: First Application of Particle Swarm Optimization. Universe 2024, 10, 96.
Zou, X.-B.; Mohanty, S.D.; Luo, H.-G.; Liu, Y.-X. Swarm Intelligence Methods for Extreme Mass Ratio Inspiral Search: First Application of Particle Swarm Optimization. Universe2024, 10, 96.
Zou, X.-B.; Mohanty, S.D.; Luo, H.-G.; Liu, Y.-X. Swarm Intelligence Methods for Extreme Mass Ratio Inspiral Search: First Application of Particle Swarm Optimization. Universe 2024, 10, 96.
Abstract
Swarm intelligence (SI) methods are nature-inspired metaheuristics for global optimization that exploit a coordinated stochastic search strategy by a group of agents. Particle Swarm Optimization (PSO) is an established SI method that has been applied successfully to the optimization of rugged high-dimensional likelihood functions, a problem that presents the main bottleneck across a variety of gravitational wave (GW) data analysis challenges. We present results from a first application of PSO to one of the most difficult of these challenges, namely, the search for Extreme Mass Ratio Inspiral (EMRI) in data from future spaceborne GW detectors such as LISA, Taiji, or Tianqin. We use the standard Generalized Likelihood Ratio Test formalism, with minimal use of restrictive approximations, to search 6 months of simulated LISA data and quantify the search depth, in signal-to-noise ratio (SNR), and breadth, in the ranges of the EMRI parameters, that PSO can handle. Our results demonstrate that a PSO-based EMRI search is successful over a search region that is in the ballpark of the one that current hierarchical schemes can identify. Directions for future improvements, including computational bottlenecks to be overcome, are identified.
Keywords
LISA; Gravitational Waves; EMRI; PSO; Likelihood Ratio
Subject
Physical Sciences, Astronomy and Astrophysics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
