Abstract

As Einstein’s equations for binary compact object inspiral have only been approximately or intermittently solved by analytic or numerical methods, the models used to infer parameters of gravitational wave (GW) sources are subject to waveform modeling uncertainty. We illustrate these differences and then introduce a very efficient technique to marginalize over waveform uncertainties, relative to a prespecified sequence of waveform models. We also extend this technique to include dynamic weighting by calculating overlap of models with Numerical Relativity. Being based on RIFT, a very efficient parameter inference engine, our technique can directly account for any available models, including very accurate but computationally costly waveforms. Our evidence and likelihood-based method works robustly on a point-by-point basis, enabling accurate marginalization for models with strongly disjoint posteriors while simultaneously increasing the reusability and efficiency of our intermediate calculations.

Publication Date

8-2021

Document Type

Thesis

Student Type

Graduate

Degree Name

Physics (MS)

Department, Program, or Center

School of Physics and Astronomy (COS)

Advisor

George M. Thurston

Advisor/Committee Member

Richard O'Shaughnessy

Advisor/Committee Member

Carlos Lousto

Campus

RIT – Main Campus

Share

COinS