title: Uncertainty quantification for nuclear density functional theory and information content of new measurements.
abstract: Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. The example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.
authors: Department of Physics and Astronomy, Francis Marion University, Florence, South Carolina 29501, USA.|Physics Division, Lawrence Livermore National Laboratory, Livermore, California 94551, USA.
authors: J D
authors: JD
authors: McDonnell
authors: Physics Division, Lawrence Livermore National Laboratory, Livermore, California 94551, USA.
authors: N
authors: N
authors: Schunck
authors: Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
authors: D
authors: D
authors: Higdon
authors: Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA.
authors: J
authors: J
authors: Sarich
authors: Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA.
authors: S M
authors: SM
authors: Wild
authors: Department of Physics and Astronomy and NSCL/FRIB Laboratory, Michigan State University, East Lansing, Michigan 48824, USA.|Physics Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.|Institute of Theoretical Physics, Faculty of Physics, University of Warsaw, ul. Hoża 69, 00-681 Warsaw, Poland.
authors: W
authors: W
authors: Nazarewicz