activity
20072024
most citedSymmetry-guided large-scale shell-model theory

132 citations · 767 across the 27 of their papers we have counts for

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26 papers · 1 filter

nucl-th2024

Uncertainty Quantification of Collective Nuclear Observables From the Chiral Potential Parametrization

Kevin S. Becker, Kristina D. Launey, Andreas Ekström +4

We perform an uncertainty estimate of quadrupole moments and B(E2) transition rates that inform nuclear collectivity. In particular, we study the low-lying states of 6Li and 12C us…

nucl-th2023

Ab Initio Symmetry-Adapted Emulator for Studying Emergent Collectivity and Clustering in Nuclei

Kevin S. Becker, Kristina D. Launey, Andreas Ekström +1

We discuss emulators from the ab initio symmetry-adapted no-core shell-model framework for studying the formation of alpha clustering and collective properties without effective ch…

nucl-th2021★ 6 cited

Symmetry and shape coexistence in 10Be

M. A. Caprio, A. E. McCoy, P. J. Fasano +1

Within the low-lying spectrum of 10Be, multiple rotational bands are found, with strikingly different moments of inertia. A proposed interpretation has been that these bands variou…

nucl-th2021★ 38 cited

Emergent symplectic symmetry in atomic nuclei: Ab initio symmetry-adapted no-core shell model

Kristina D Launey, Tomáš Dytrych, Grigor H Sargsyan +2

Exact symmetry and symmetry-breaking phenomena play a key role in gaining a better understanding of the physics of many-particle systems, from quarks and atomic nuclei, through mol…

nucl-th2021★ 57 cited

Nuclear Dynamics and Reactions in the Ab Initio Symmetry-Adapted Framework

Kristina D. Launey, Alexis Mercenne, Tomas Dytrych

We review the ab initio symmetry-adapted (SA) framework for determining the structure of stable and unstable nuclei, along with related electroweak, decay and reaction processes. T…

nucl-th2021★ 22 cited

Machine learning approach to pattern recognition in nuclear dynamics from the ab initio symmetry-adapted no-core shell model

O. M. Molchanov, K. D. Launey, A. Mercenne +3

A novel machine learning approach is used to provide further insight into atomic nuclei and to detect orderly patterns amidst a vast data of large-scale calculations. The method ut…