Numerical relativity surrogate waveform model for precessing binary black holes

Numerical relativity (NR) simulations are required to accurately predict the gravitational waveform from the merger of binary black holes. Unfortunately, NR simulations are very expensive and cannot be used directly in parameter estimation. Surrogate modeling is a data-driven approach to modeling, that has been shown to be both fast and accurate in reproducing NR simulations. We present a new 7-dimensional surrogate model for the waveforms of generically precessing binary black holes, with mass ratios as high as 4. Trained directly against hundreds of NR simulations, these models are shown to reproduce the simulations nearly as accurately as the simulations themselves.