Error analysis in nuclear density functional theory

被引：45

作者：

Schunck, Nicolas ^{[1
]}

McDonnell, Jordan D. ^{[1
]}

Sarich, Jason ^{[2
]}

Wild, Stefan M. ^{[2
]}

Higdon, Dave ^{[3
]}

机构：

[1] Lawrence Livermore Natl Lab, Div Phys, Livermore, CA 94551 USA

[2] Argonne Natl Lab, Div Math & Comp Sci, Argonne, IL 60439 USA

[3] Los Alamos Natl Lab, Los Alamos, NM 87545 USA

来源：

JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS | 2015年 / 42卷 / 03期

关键词：

nuclear structure; uncertainty quantification; density functional theory; high performance computing; energy functional; Bayesian statistics; covariance; MEAN-FIELD THEORY; PARAMETER-ESTIMATION; EQUATIONS; MODELS;

D O I：

10.1088/0954-3899/42/3/034024

中图分类号：

O57 [原子核物理学、高能物理学];

学科分类号：

070202 ;

摘要：

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.

引用

页数：16

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