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Physical Sciences and Mathematics Commons

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Astrophysics and Astronomy

Physics and Astronomy Faculty Publications and Presentations

2024

LISA

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Full-Text Articles in Physical Sciences and Mathematics

Search For Extreme Mass Ratio Inspirals Using Particle Swarm Optimization And Reduced Dimensionality Likelihoods, Xiao-Bo Zou, Soumya Mohanty, Hong-Gang Luo, Yu-Xiao Liu Apr 2024

Search For Extreme Mass Ratio Inspirals Using Particle Swarm Optimization And Reduced Dimensionality Likelihoods, Xiao-Bo Zou, Soumya Mohanty, Hong-Gang Luo, Yu-Xiao Liu

Physics and Astronomy Faculty Publications and Presentations

Extreme-mass-ratio inspirals (EMRIs) are significant observational targets for spaceborne gravitational wave detectors, namely, LISA, Taiji, and Tianqin, which involve the inspiral of stellar-mass compact objects into massive black holes (MBHs) with a mass range of approximately 104 ∼107𝑀⊙ . EMRIs are estimated to produce long-lived gravitational wave signals with more than 105 cycles before plunge, making them an ideal laboratory for exploring the strong-gravity properties of the spacetimes around the MBHs, stellar dynamics in galactic nuclei, and properties of the MBHs itself. However, the complexity of the waveform model, which involves the superposition of multiple harmonics, as well as the …


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 Feb 2024

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, …