物理学报2023，Vol.72Issue(18)：147-157,11.DOI:10.7498/aps.72.20230702
基于深度学习的钻孔辐射压离子加速建模
Modeling of ion accelerated by borehole radiation pressure based on deep learning
摘要
关键词
激光离子加速/神经网络Key words
laser-driven ion acceleration/neural Networks引用本文复制引用
张普渡,王伟权,李哲民,张资旋,王叶晨,周泓宇,银燕..基于深度学习的钻孔辐射压离子加速建模[J].物理学报,2023,72(18):147-157,11.基金项目
国家自然科学基金青年基金(批准号:12005298)、国家自然科学基金联合项目"叶企孙"科学基金(批准号:U2241281)、湖南省自然科学基金(批准号:2022JJ30656)、湖南省自然科学基金青年基金(批准号:2021JJ40661)和国防科技大学科研计划(批准号:ZK19-25)资助的课题.Project supported by the Young Scientists Fund of the National Natural Science Foundation of China(Grant No.12005298),the"Ye Qisun"Science Fund of the National Natural Science Foundation of China(Grant No.U2241281),the Natural Science Foundation of Hunan Province,China(Grant No.2022JJ30656),the Young Scientists Fund of the National Natural Science Foundation of Hunan Province,China(Grant No.2021JJ40661),and the Research Programm of NUDT(Grant No.ZK 19-25). （批准号:12005298）
