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Emergent symmetries in atomic nuclei: Probing nuclear dynamics and physics beyond the standard model
by K. D. Launey, K. S. Becker, G. H. Sargsyan, O. M. Molchanov,M. Burrows,A. Mercenne, T. Dytrych, D. Langr, J. P. Draayer
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Submission summary
Authors (as registered SciPost users): | Kristina Launey |
Submission information | |
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Preprint Link: | scipost_202212_00037v1 (pdf) |
Date submitted: | 2022-12-17 01:58 |
Submitted by: | Launey, Kristina |
Submitted to: | SciPost Physics Proceedings |
Proceedings issue: | 34th International Colloquium on Group Theoretical Methods in Physics (GROUP2022) |
Ontological classification | |
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Academic field: | Physics |
Specialties: |
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Approach: | Theoretical |
Abstract
Dominant shapes naturally emerge in atomic nuclei from first principles, thereby establishing the shape-preserving symplectic Sp(3,R) symmetry as remarkably ubiquitous and almost perfect symmetry in nuclei. We discuss the critical role of this emergent symmetry in enabling machine-learning descriptions of heavy nuclei, ab initio modeling of alpha clustering and collectivity, as well as tests of beyond-the-standard-model physics. In addition, the Sp(3,R) and SU(3) symmetries provide relevant degrees of freedom that underpin the ab initio symmetry-adapted no-core shell model with the remarkable capability of reaching nuclei and reaction fragments beyond the lightest and close-to-spherical species.
Current status:
Reports on this Submission
Report #1 by Anonymous (Referee 1) on 2023-1-14 (Invited Report)
- Cite as: Anonymous, Report on arXiv:scipost_202212_00037v1, delivered 2023-01-14, doi: 10.21468/SciPost.Report.6533
Strengths
This first part of this manuscript (Sections 1 and 2) consists of a pedagogical review of the SU(3) model of Elliott, the symplectic Sp(3,R) model of Rowe and Rosensteel, as well as of the Symmetry Adapted No Core Shell Model of the LSU group. The second part of the manuscript (Section 3) gives a brief account of the three most recent developments based on the above approach, which are related to the machine learning approach for the prediction of nuclear observables of heavy nuclei through neural networks trained for low nuclei, the study of clustering in relation to nuclear beta decay, and the determination of optical model potentials for nuclear reactions.
Weaknesses
none
Report
I think that this manuscript can be useful to readers wishing to be quickly informed on the recent developments related to applications of the SU(3) and symplectic symmetries in nuclear physics, without having to go through a long review paper. The paper is very well written and contains a large amount of useful references. Therefore I am happy to recommend publication in its present form.
Requested changes
A couple of misprints to be fixed before publication are listed below.
Line 104. “with spin” instead of “with spins”.
Line 154. “orbital angular momentum” instead of “orbital momentum”.
The titles are missing in Refs. [6,8,16,23,36,37,38,47,43].