Uncertainty quantification of a computer model for binary black hole formation

@article{Lin2021UncertaintyQO,
  title={Uncertainty quantification of a computer model for binary black hole formation},
  author={Luyao Lin and Derek R. Bingham and Floor S. Broekgaarden and Ilya Mandel},
  journal={The Annals of Applied Statistics},
  year={2021}
}
In this paper, a fast and parallelizable method based on Gaussian Processes (GPs) is introduced to emulate computer models that simulate the formation of binary black holes (BBHs) through the evolution of pairs of massive stars. Two obstacles that arise in this application are the a priori unknown conditions of BBH formation and the large scale of the simulation data. We address them by proposing a local emulator which combines a GP classifier and a GP regression model. The resulting emulator… 
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