Error analysis in nuclear density functional theory

Nicolas Schunck, Jordan D. McDonnell, Jason Sarich, Stefan M. Wild, Dave Higdon

Research output: Contribution to journalArticlepeer-review

51 Scopus citations

Abstract

Nuclear density functional theory (DFT) is the only microscopic, global approach to the structure of atomic nuclei. It is used in numerous applications, from determining the limits of stability to gaining a deep understanding of the formation of elements in the Universe or the mechanisms that power stars and reactors. The predictive power of the theory depends on the amount of physics embedded in the energy density functional as well as on efficient ways to determine a small number of free parameters and solve the DFT equations. In this article, we discuss the various sources of uncertainties and errors encountered in DFT and possible methods to quantify these uncertainties in a rigorous manner.

Original languageEnglish
Article number034024
JournalJournal of Physics G: Nuclear and Particle Physics
Volume42
Issue number3
DOIs
StatePublished - Mar 1 2015
Externally publishedYes

Keywords

  • Bayesian statistics
  • covariance
  • energy functional
  • high performance computing
  • nuclear structure
  • uncertainty quantification-density functional theory

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