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 language | English |
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Article number | 034024 |
Journal | Journal of Physics G: Nuclear and Particle Physics |
Volume | 42 |
Issue number | 3 |
DOIs | |
State | Published - Mar 1 2015 |
Externally published | Yes |
Keywords
- Bayesian statistics
- covariance
- energy functional
- high performance computing
- nuclear structure
- uncertainty quantification-density functional theory