Uncertainty quantification of an empirical shell-model interaction using principal component analysis
| Autor: | Calvin W. Johnson, Rodrigo Navarro Perez, Jordan M. R. Fox |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Physics
Hessian matrix Propagation of uncertainty Nuclear Theory FOS: Physical sciences Observable Probability and statistics Computational Physics (physics.comp-ph) Parameter space Nuclear Theory (nucl-th) symbols.namesake Physics - Data Analysis Statistics and Probability Principal component analysis symbols Statistical physics Uncertainty quantification Linear combination Physics - Computational Physics Data Analysis Statistics and Probability (physics.data-an) |
| Popis: | 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 $1s$-$0d$ 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. 30 pages, 11 figures, 2 tables |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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