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arXiv · 2109.01388

Bayesian evaluation of residual production cross sections in proton induced spallation reactions

Peng Dan·Hui-Ling Wei·Xi-Xi Chen·Xiao-Bao Wei·Yu-Ting Wang·Jie Pu·Kai-Xuan Cheng·Chun-Wang Ma
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Abstract

The Bayesian neural network (BNN) method is used to construct a predictive model for fragment prediction of proton induced spallation reactions with the guidance of a simplified EPAX formula. Compared to the experimental data, it is found that the BNN + sEPAX model can reasonably extrapolate with less information compared with BNN method. The BNN + sEPAX method provides a new approach to predict the energy-dependent residual cross sections produced in proton-induced spallation reactions from tens of MeV/u up to several GeV/u.

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Peng Dan, Hui-Ling Wei, Xi-Xi Chen, Xiao-Bao Wei, Yu-Ting Wang, Jie Pu, Kai-Xuan Cheng, Chun-Wang Ma. 2021-09-03. Bayesian evaluation of residual production cross sections in proton induced spallation reactions. https://doi.org/10.1088/1361-6471%2Fac7069

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