Gravitational-wave source dynamics and population inference

Mould, Matthew ORCID: 0000-0001-5460-2910 (2023). Gravitational-wave source dynamics and population inference. University of Birmingham. Ph.D.

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Abstract

Gravitational-wave astronomy has yielded an unprecedented treasure trove of scientific discoveries in recent years, from the first detection of a black-hole merger and strong-field tests of gravity, to the observation of colliding neutron stars and corresponding global multi-messenger followup. The future yet holds great promise. As the observational catalogue continues to grow in the coming years with improvements in sensitivity and the introduction of new detectors, our available inferential power in the gravitational landscape of the universe will grow in tandem. In this Thesis, we leverage this increasingly informative dataset to investigate the evolution of binary black holes from formation to merger, deriving new results on the influence of astrophysics and relativity on binary inspirals and, conversely, revealing constraints from gravitational-wave observables on the past lives of observed sources. We place a particular focus on Bayesian methods in analysing gravitational-wave catalogues and use targeted models, simulation-based inference, and deep learning to measure the properties of the astrophysical population of merging binary black holes. Our work highlights the crucial interplay between compact-binary formation, relativistic dynamics, and statistical inference. The tools we develop will enable deeper astrophysical insights as gravitational-wave astronomy enters into the big-data era.

Type of Work:

Thesis (Doctorates > Ph.D.)

Award Type:

Doctorates > Ph.D.

Supervisor(s):