Physical Sciences and Mathematics Commons^™

Characterizing And Mitigating Transient Noise In Ligo Observatories For Gravitational Wave Detection, Jane Glanzer

LSU Doctoral Dissertations

The existence of gravitational waves is predicted by Albert Einstein's Theory of General Relativity. Commonly referred to as "ripples in spacetime", these waves are generated by some of the most violent and energetic processes in the universe. Despite their theoretical prediction over a century ago, it wasn't until 2015 that the Advanced LIGO (aLIGO) interferometers in Hanford, WA and Livingston, LA directly detected gravitational waves for the first time, confirming Einstein's theory and ushering in a new era of astrophysics.

Detecting gravitational waves requires incredible precision. Because of the extreme sensitivity required, it is possible for the gravitational wave data …

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, …