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Swarm Intelligence Methods For Extreme Mass Ratio Inspiral Search: First Application Of Particle Swarm Optimization, Xiao-Bo Zou, Soumya D. Mohanty, Hong-Gang Luo, Yu-Xiao Liu

Physics and Astronomy Faculty Publications and Presentations

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 represents the main bottleneck across a variety of gravitational wave (GW) data analysis challenges. We present results from the first application of PSO to one of the most difficult of these challenges, namely the search for the Extreme Mass Ratio Inspiral (EMRI) in data from future spaceborne GW detectors such as LISA, Taiji, …