How well do we know the neutron-matter equation of state (EOS) at the densities inside neutron stars? And the nuclear saturation properties of symmetric matter? Chiral effective field theory (EFT) is widely used to predict the nuclear-matter EOS. What is needed now are statistically meaningful comparisons between nuclear theory and recent observational constraints, e.g., from NICER and direct detection of gravitational waves.
In this talk I report on the BUQEYE collaboration's  recent statistical analysis of EFT truncation errors in the infinite-matter EOS derived from chiral EFT [2,3]. Bayesian machine learning, via Gaussian Processes with physics-based hyperparameters, allows us to efficiently quantify and propagate theoretical uncertainties of the EOS (such as correlated EFT truncation errors) to derived quantities. In particular, I will explain why an understanding of truncation-error correlations between different densities and observables is crucial for reliable EOS uncertainty quantification.
 Drischler, Furnstahl, Melendez, and Phillips, arXiv:2004.07232
 Drischler, Melendez, Furnstahl, and Phillips, arXiv:2004.07805
Zoom link will be available via announcement email, or by contacting: stroberg[at]uw.edu.