Uncertainty Quantification and Propagation in Nuclear Density Functional Theory
Nuclear density functional theory (DFT) is one of the main theoretical tools used to study the properties of heavy and superheavy elements, or to describe the structure of nuclei far from stability. While on-going eff orts seek to better root nuclear DFT in the theory of nuclear forces, energy functionals remain semi-phenomenological constructions that depend on a set of parameters adjusted to experimental data in fi nite nuclei. In this paper, we review recent eff orts to quantify the related uncertainties, and propagate them to model predictions. In particular, we cover the topics of parameter estimation for inverse problems, statistical analysis of model uncertainties and Bayesian inference methods. Illustrative examples are taken from the literature.
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- Conference: Presented at: Perspectives on Nuclear Data for the Next Decade, Bruyeres-le-Chatel, France, Oct 14 - Oct 17, 2014
- Research Org:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
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- Country of Publication:
- United States
- 73 NUCLEAR PHYSICS AND RADIATION PHYSICS; 97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
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