A binary black hole waveform generator trained on numerical relativity waveforms

Ik Siong Heng
University of Glasgow

The detection of GW150914, and subsequent gravitational waves signals, poses a substantial data analysis problem. Some of the most sensitive methods for extracting signals and parameter estimation on those signals require prior knowledge of the signal morphology. In the case of compact binary coalescence, this prior information is obtained from numerical relativity simulations. These simulations are both expensive and time-consuming to produce and consequently only a small region of the overall parameter space has been probed. We present a method, based on Gaussian process regression, which is capable of placing a prior probability distribution over the entire compact binary coalescence parameter space, allowing us to produce interpolated waveforms with an associated measure of the interpolation uncertainty.

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