English

Uncertainty quantification of an empirical shell-model interaction using principal component analysis

Nuclear Theory 2020-05-20 v3 Computational Physics Data Analysis, Statistics and Probability

Abstract

Recent investigations have emphasized the importance of uncertainty quantification (UQ) to describe errors in nuclear theory. We carry out UQ for configuration-interaction shell model calculations in the 1s1s-0d0d valence space, investigating the sensitivity of observables to perturbations in the 66 parameters (matrix elements) of a high-quality empirical interaction. The large parameter space makes computing the corresponding Hessian numerically costly, so we compare a cost-effective approximation, using the Feynman-Hellmann theorem, to the full Hessian and find it works well. Diagonalizing the Hessian yields the principal components of the interaction: linear combinations of parameters ordered by sensitivity. This approximately decoupled distribution of parameters facilitates theoretical error propagation onto structure observables: electromagnetic transitions, Gamow-Teller decays, and dark matter-nucleus scattering matrix elements.

Keywords

Cite

@article{arxiv.1911.05208,
  title  = {Uncertainty quantification of an empirical shell-model interaction using principal component analysis},
  author = {Jordan M. R. Fox and Calvin W. Johnson and Rodrigo Navarro Perez},
  journal= {arXiv preprint arXiv:1911.05208},
  year   = {2020}
}

Comments

30 pages, 11 figures, 2 tables

R2 v1 2026-06-23T12:13:44.065Z