Date of Award
2026
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Physics
Department
Physics
First Advisor
Gaurav Khanna
Abstract
Extracting astrophysical information from gravitational-wave data is essentially an inverse problem: a source's parameters are inferred by repeatedly comparing the observed signal against modeled waveforms. Reliability of the science depends directly on those models, which must be accurate, fast to evaluate, and valid across a broad region of parameter space to support future-generation detectors. Yet no single model achieves all three, and the difficulty is greatest in the intermediate-mass-ratio regime, where numerical relativity (NR) becomes prohibitively expensive and perturbative methods are not fully established. This dissertation advances gravitational-wave waveform modeling along three axes: coverage, efficiency, and fidelity.
The central contribution is BHPTNRSur2dq1e3, a reduced-order surrogate model built from point-particle black-hole perturbation theory and calibrated against a sparse set of NR simulations. The model spans mass ratios from q = 3 to 1000 and includes the spin of the primary black hole, reaching a region of parameter space inaccessible to NR-trained models while remaining fast enough for use in parameter estimation. The dissertation further extends the surrogate construction framework to include precessing systems, applied to a small body on a shallow inclined orbit about a spinning primary.
To address fidelity, the dissertation introduces a framework that represents the calibration uncertainty of a waveform model probabilistically and marginalizes over it during inference. By propagating this uncertainty into the analysis, biases that would otherwise be mistaken for properties of the source are instead absorbed as modeling uncertainty, yielding measurements that more honestly reflect what the model does and does not constrain.
Together, these contributions extend waveform modeling into the regime that next-generation detectors will probe most deeply, making the gravitational-wave inverse problem more reliably solvable across a broader region of parameter space.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Bachhar, Ritesh, "ADVANCING GRAVITATIONAL WAVE MODELING FOR BINARY BLACK HOLES: EXPANDING PARAMETER SPACE AND QUANTIFYING UNCERTAINTY" (2026). Open Access Dissertations. Paper 4594.
https://digitalcommons.uri.edu/oa_diss/4594