School of Physics Thesis Dissertation Defense

Chad Henshaw 
Advisor: Dr. Laura Cadonati, School of Physics, Georgia Institute of Technology

Extracting Black Hole Phenomena from Gravitational Waves 
Date: Friday, June 20, 2025 
Time:  11:00 a.m.   
Location: Howey N2021/202 
Zoom link: https://gatech.zoom.us/j/91968470385?pwd=uhl6zC54mykHedIGioOI3a4mOfB1pR…

Committee Members:
Dr. Tamara Bogdanović, School of Physics, Georgia Institute of Technology
Dr. Nepomuk Otte, School of Physics, Georgia Institute of Technology
Dr. Surabhi Sachdev, School of Physics, Georgia Institute of Technology
Dr. Richard O’Shaughnessy, School of Mathematics and Statistics, Rochester Institute of Technology

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 ten years 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 source 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 phenomena exhibited by BBH systems are discussed over the course of three projects.

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 presents the implementation of 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 based on initial conditions they 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 and the variation of modal content. The results of this study show that correlation between time-frequency features and the horizon dynamics is plausible, and a route towards `imaging' black holes is discussed.