Extracting Black Hole Phenomena from Gravitational Waves
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Henshaw, Chad
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Abstract
On the 14th of September 2015, the Laser Interferometer Gravitational-Wave Observatory
(LIGO) made the first detection of a gravitational wave (GW) signal from the merger of two
black holes, marking the start of a new era in our quest to understand gravity, the universe,
and the nature of reality. In the decade since, the LIGO/Virgo/KAGRA Collaboration has
detected over 200 gravitational wave events, primarily from the mergers of binary black hole
(BBH) systems. Measurements of a GW signal through Bayesian inference yield statistical
information on the parameters of their originating system, offering insight into the properties,
characteristics, and dynamics of the progenitor black holes. Herein, methods for extracting
information from GW signals related to BBH system phenomena are discussed over the
course of three original projects of my design.
The first project analyzes the precession of the binary’s orbital plane, which occurs when
the black hole spins are misaligned relative to the orbital angular momentum. An implementation of different ways to parameterize the precession in RIFT - an iterative parameter
estimation algorithm for analyzing GW data - is presented. It is shown that the interpretation of the inferred precession depends strongly on its parameterization if both spins are
misaligned, and methods are developed to leverage this dependence in the operation of RIFT.
The second project implements the first comprehensive parameter estimation infrastructure
for measuring the source properties from systems of initially unbound black holes that make
close hyperbolic encounters. Such systems exhibit diverse waveform morphology, and can
either scatter, dynamically capture after multiple flybys, or directly plunge to merger. It is
shown that with this implementation, RIFT can accurately recover the source parameters
of these systems.
The final project investigates how the geometry of the horizon that forms when two black
holes merge may be encoded within the time-frequency representation of signals from BBH
systems. First, methods are developed for visualizing time-frequency structure using the
continuous wavelet transform (CWT), utilizing both sine-Gaussian wavelets and ‘chirplets’
- sine-Gaussian wavelets that evolve in frequency. Second, the CWT is used to analyze
the post-merger signal from BBH systems with asymmetric mass ratio under a variety of
scenarios, including both aligned and precessing spin. This study shows that correlation
between time-frequency features and the horizon dynamics is plausible, and a route towards
‘imaging’ black holes is discussed.
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Date
2025-08-13
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Text
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Dissertation (PhD)