Constraining the Woods-Saxon potential in fusion reactions based on the neural network
| Autor: | Gao, Zepeng, Liu, Siyu, Wen, Peiwei, Liao, Zehong, Yang, Yu, Su, Jun, Wang, Yongjia, Zhu, Long |
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| Rok vydání: | 2023 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| DOI: | 10.1103/PhysRevC.109.024601 |
| Popis: | The accurate determination of the nuclear interaction potential is essential for predicting the fusion cross sections and understanding the reaction mechanism, which plays an important role in the synthesis of superheavy elements. In this work, the neural network, which combines with the calculations of the fusion cross sections via the Hill-Wheeler formula, is developed to optimize the parameters of the Woods-Saxon potential by comparing the experimental values. The correlations between the parameters of Woods-Saxon potential and the reaction partners, which can be quantitatively fitted to a sigmoid-like function with the mass numbers, have been displayed manifestly for the first time. This study could promote the accurate estimation of nucleus-nucleus interaction potential in low energy heavy-ion collisions. Comment: 6 pages, 5 figures |
| Databáze: | arXiv |
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