Uma Raghavan

Estimating the Mass and Distance of Black Holes from LIGO Data

Started May 2, 2024

Abstract or project description

Gravitational waves, ripples in spacetime caused by accelerating massive objects, offer a new way to explore the universe and phenomena such as black hole mergers. Since their first detection in 2015 by the Laser Interferometer Gravitational-Wave Observatory (LIGO), these waves have become a crucial tool for understanding cosmic events that are otherwise inaccessible. This study analyzes gravitational wave signals from three distinct black hole mergers, GW150914, GW190521, and GW170814, to estimate key parameters such as the masses and luminosity distances of the merging black holes, using Bayesian statistics and Markov Chain Monte Carlo (MCMC) methods. With the Bilby and Dynesty frameworks, I generated corner plots three times to visualize parameter probabilities, focusing on chirp mass, mass ratio, and luminosity distance, each time with a different phase value. This analysis reveals that variations in the phase parameter significantly impact the estimated values in similar ways, particularly for GW150914 and GW190521, while GW170814 shows more stability due to fewer variable parameters. However, limitations come from estimating only a few parameters rather than the full set, skewing the results. These findings highlight the complexity of gravitational wave parameter estimation and the need for improved methods to enhance the accuracy of future measurements, ultimately advancing our understanding of the cosmos and the fundamental nature of gravity.