Assessing and marginalizing over compact binary coalescence waveform systematics with RIFT

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. Using a simple scenario, we illustrate these differences, then introduce a very efficient technique to marginalize over waveform uncertainties, relative to a pre-specified sequence of waveform models. 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.