Characterisation of Particle Swarm Optimisation Based Detection Pipeline for Gravitational Waves from Binary Black Hole Mergers

Bhuvanambiga, P. (2022) Characterisation of Particle Swarm Optimisation Based Detection Pipeline for Gravitational Waves from Binary Black Hole Mergers. Masters thesis, Indian Institute of Science Education and Research Kolkata.

Text (MS dissertation of Bhuvanambiga P (17MS053)) 17MS053_Thesis_file.pdf - Submitted Version Restricted to Repository staff only Download (6MB)

Abstract

We discuss the performance of the Particle Swarm Optimisation (PSO) algorithm in the detection and parameter estimation of gravitational wave signals from binary black hole mergers. We specifically discuss it in the context of binary black holes where the masses fall in the range of 20 - 60 M⊙. We discuss the standard PSO algorithm, and analyse if and how the SNR, and estimated mass parameters depend on the number of steps, number of particles and number of swarms involved in the algorithm. We then discuss the performance of a mass-eigen based variation of the PSO algorithm, and compare its performance with standard PSO.

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