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MACHINE LEARNING IN THE PROBLEM OF NO CORE SHELL MODEL RESULT EXTRAPOLATIONS
- Authors: Sharypov R.E.1, Mazur A.I.1, Shirokov A.M.2
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Affiliations:
- Pacific National University
- Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics
- Issue: Vol 88, No 1 (2025)
- Pages: 151–160
- Section: PROCEEDINGS OF 74TH INTERNATIONAL CONFERENCE ON NUCLEAR PHYSICS “NUCLEUS-2024: FUNDAMENTAL PROBLEMS AND APPLICATIONS”, 1–5 JULY 2024, DUBNA, RUSSIA. Nuclei. Theory
- URL: https://journals.rcsi.science/0044-0027/article/view/303738
- DOI: https://doi.org/10.31857/S0044002725010187
- EDN: https://elibrary.ru/GQLEMT
- ID: 303738
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Abstract
A method for extrapolating the results of variational calculations to the case of the infinite basis using an ensemble of artificial neural networks is proposed. Extrapolations of the no-core shell model results obtained with nucleon-nucleon interaction Daejeon16 for the ground state energies, as well as for the rootmean-square point-proton, point-neutron and point-nucleon (matter) radii of the 6Li and 6He nuclei, are performed.
About the authors
R. E. Sharypov
Pacific National University
Email: amazur.pnu.khb@mail.ru
Khabarovsk, Russia
A. I. Mazur
Pacific National University
Email: amazur.pnu.khb@mail.ru
Khabarovsk, Russia
A. M. Shirokov
Lomonosov Moscow State University, Skobeltsyn Institute of Nuclear Physics
Author for correspondence.
Email: amazur.pnu.khb@mail.ru
Moscow, Russia
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