Global prediction of nuclear charge density distributions using a deep neural network-Reference-Cited by-同舟云学术

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Global prediction of nuclear charge density distributions using a deep neural network

Published:2024-07-02 Issue:1 Volume:110 Page:
ISSN:2469-9985
Container-title:Physical Review C
language:en
Short-container-title:Phys. Rev. C

Author:

Shang Tian Shuai¹^ORCID,Xie Hui Hui²³^ORCID,Li Jian²³^ORCID,Liang Haozhao²³^ORCID

Affiliation:

1. Jilin University

2. The University of Tokyo

3. RIKEN

Funder

Natural Science Foundation of Jilin Province

National Natural Science Foundation of China

Japan Society for the Promotion of Science

RIKEN

Publisher

American Physical Society (APS)

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevC.110.014308/fulltext

Reference96 articles.

1. Self-consistent mean-field models for nuclear structure

2. Possible Existence of a Neutron

3. Coexistence in even-mass nuclei

4. Determination of the neutron skin thickness from interaction cross section and charge-changing cross section for B, C, N, O, F isotopes

5. Neutron rich matter in the laboratory and in the heavens after GW170817

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Determination of electron screening potential of 6Li(p, α)3He reaction using Multi Layer Perceptron based neural network;Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms;2024-12

2. Global prediction of nuclear charge density distributions using a deep neural network;Physical Review C;2024-07-02

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