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利用机器学习预测重核和超重核的α衰变能

Prediction onα-decay Energy of Heavy and Superheavy Nuclei Using Machine Learning
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摘要 α衰变对重核和超重核的鉴别和研究有重要意义。近年来,机器学习广泛应用于各种核物理问题研究。为进一步探索机器学习在核物理问题研究中的适用性,本文采用机器学习中的高斯过程对重核和超重核的α衰变能进行了研究。首先,在高斯过程的框架下计算了新核素207Th的α衰变能,计算得到的理论α衰变能与实验结果符合较好,结合较好的交叉验证结果可知,利用高斯过程研究重核和超重核α衰变能的可靠性较好。然后,利用高斯过程预测了89≤Z≤118的一些重核和超重核未知的α衰变能,并将该预测结果与传统模型的预测结果进行了比较,二者符合较好。综上所述,这些预测的α衰变能可为未来重核和超重核的实验研究提供较准确的理论参考。 α-decay is one of the most dominant decay modes of unstable nuclei.It is helpful for the investigation of exotic nuclear structures.Moreover,α-decay is a powerful tool for identifying the newly synthesized nuclides for heavy and superheavy nuclei in the experiment.It is of vital importance to propose more theoretical models to provide more accurate predictions onα-decay properties.Recently,machine learning is widely applied to investigate various essential problems in nuclear physics.As one of the popular machine learning algorithms,the Gaussian process is successfully used in the studies of theα-decay properties of some neutron-deficient actinide nuclei.It is of great interest to probe the feasibility of the Gaussian process in the studies ofα-decay properties for nuclei in more nuclear regions.In this work,the Gaussian process was extended to study theα-decay energy of heavy and superheavy nuclei.Two common kernel functions named the Matérn 3/2 kernel function and the Matérn 5/2 kernel function,were used in the calculations.First,theα-decay energy of the new nuclide 207 Th was calculated using the Gaussian process.The deviations between the theoreticalα-decay energy calculated using the Gaussian process with two different kernel functions and the experimental one are 0.025 MeV and 0.060 MeV,respectively.The small deviations show that the calculatedα-decay energy is in good accord with the experimental data,which demonstrates that the Gaussian process is reliable for the studies ofα-decay energy when combined with the good cross-validation results.Besides,it is found that there would be slightly better results when calculatingα-decay energy using the Gaussian process with the Matérn 3/2 kernel function.The reason may be that the Matérn 3/2 kernel function is smoother than the Matérn 5/2 kernel function.Due to the small change ofα-decay energy for heavy and superheavy nuclei,the Matérn 3/2 kernel function is more suitable for the calculation of them.Then,the unknownα-decay energy for some heavy and superheavy nuclei with 89≤Z≤118 was predicted using the Gaussian process,and the predictedα-decay energy was compared with that calculated using the traditional models.It is found that the theoretical results calculated using the Gaussian process show good agreement with those calculated using the traditional models.Furthermore,the predictedα-decay energy for 251 Bk,270 Sg,and 272 Hs shows the influence of the deformed shell at N=154 and the deformed subshell at N=164.The predicted results can be new references for future experiments on heavy and superheavy nuclei.
作者 袁子懿 任中洲 柏栋 王震 YUAN Ziyi;REN Zhongzhou;BAI Dong;WANG Zhen(School of Physics Science and Engineering,Tongji University,Shanghai 200092,China;Key Laboratory of Advanced Micro-Structure Materials of Ministry of Education,Shanghai 200092,China;College of Science,Hohai University,Nanjing 211100,China)
出处 《原子能科学技术》 EI CAS CSCD 北大核心 2023年第4期713-720,共8页 Atomic Energy Science and Technology
基金 国家自然科学基金(12035011,12022517,11975167,11947211,11905103,11881240623,11961141003) 国家重点研发计划(2018YFA0404403) 中央高校基本科研业务费项目(22120200101) 中国澳门科学技术发展基金(0048/2020/A1)。
关键词 Α衰变 机器学习 高斯过程 重核和超重核 α-decay machine learning Gaussian process heavy and superheavy nuclei
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