Machine Learning in the Problem of No-Core Shell Model Result Extrapolations

IF 0.4 4区 物理与天体物理 Q4 PHYSICS, NUCLEAR Physics of Atomic Nuclei Pub Date : 2025-03-03 DOI:10.1134/S1063778824700868
R. E. Sharypov, A. I. Mazur, A. M. Shirokov
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引用次数: 0

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 the nucleon–nucleon interaction Daejeon16 for the ground state energies, as well as for the root-mean-square (rms) point-proton, point-neutron, and point-nucleon (matter) radii of the \({}^{6}\)Li and \({}^{6}\)He nuclei, are performed.

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无核壳模型结果外推问题中的机器学习
提出了一种利用人工神经网络集合将变分计算结果外推到无限基情况的方法。用核子-核子相互作用Daejeon16得到的无核壳模型结果外推了基态能量,以及\({}^{6}\) Li和\({}^{6}\) He核的点质子、点中子和点核子(物质)半径的均方根(rms)。
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来源期刊
Physics of Atomic Nuclei
Physics of Atomic Nuclei 物理-物理:核物理
CiteScore
0.60
自引率
25.00%
发文量
56
审稿时长
3-6 weeks
期刊介绍: Physics of Atomic Nuclei is a journal that covers experimental and theoretical studies of nuclear physics: nuclear structure, spectra, and properties; radiation, fission, and nuclear reactions induced by photons, leptons, hadrons, and nuclei; fundamental interactions and symmetries; hadrons (with light, strange, charm, and bottom quarks); particle collisions at high and superhigh energies; gauge and unified quantum field theories, quark models, supersymmetry and supergravity, astrophysics and cosmology.
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