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Machine Learning for Extrapolating No-Core Shell Model Results to Infinite Basis

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arxiv 2504.06594 v1 pith:3AVO5BLE submitted 2025-04-09 nucl-th

R. E. Sharypov (1) , A. I. Mazur (1) , A. M. Shirokov (2) ((1) Pacific National University , Russia , (2) Skobeltsyn Institute of Nuclear Physics , Lomonosov Moscow State University , Moscow , Russia) This is my paper · ORCID
classification nucl-th
keywords modelresultsenergiesinfinitelearningmachinencsmno-core
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We utilize the machine learning to extrapolate to the infinite model space the no-core shell model (NCSM) results for the energies and rms radii of the 6He ground state and 6Li lowest states. The extrapolated energies and rms radii converge as the NCSM results from larger model spaces are included in the training dataset for ensemble of artificial neural networks thus enabling an accurate predictions for these observables.

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  1. Multishell Dirac fermions in the Einstein-Dirac system

    gr-qc 2025-07 conditional novelty 6.0 of 10

    Multishell solutions of the spherically symmetric Einstein-Dirac system are constructed for 2, 6, 12, and 20 fermions.

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