Error Analysis in Nuclear Density Functional Theory

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.

18 pages, 3 figures, 4 tables; Invited paper for the Journal of Physics G: Nuclear and Particle Physics focus section entitled "Enhancing the interaction between nuclear experiment and theory through information and statistics"; Revised version after comments by the referees: Figure 1 and Table 4 have been corrected

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Cited by in corpus (5)

• Uncertainty Quantification for Nuclear Density Functional Theory and Information Content of New Measurements
• A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive Model
• Uncertainty Quantification for Optical Model Parameters
• Solution of Hartree-Fock-Bogoliubov equations and fitting procedure using N2LO Skyrme pseudo-potential in spherical symmetry
• Statistical errors in Weizsaecker-Skyrme mass model