摘要
The Bayesian neural network(BNN)method is proposed to predict the isotopic cross-sections in proton induced spallation reactions.Learning from more than 4000 data sets of isotopic cross-sections from 19 experimental measurements and 5 theoretical predictions with the SPACS parametrization,in which the mass of the spallation system ranges from 36 to 238,and the incident energy from 200 MeV/u to 1500 MeV/u,it is demonstrated that the BNN method can provide good predictions of the residue fragment cross-sections in spallation reactions.
The Bayesian neural network(BNN) method is proposed to predict the isotopic cross-sections in proton induced spallation reactions.Learning from more than 4000 data sets of isotopic cross-sections from 19 experimental measurements and 5 theoretical predictions with the SPACS parametrization,in which the mass of the spallation system ranges from 36 to 238,and the incident energy from 200 MeV/u to 1500 MeV/u,it is demonstrated that the BNN method can provide good predictions of the residue fragment cross-sections in spallation reactions.
作者
Chun-Wang Ma
Dan Peng
Hui-Ling Wei
Zhong-Ming Niu
Yu-Ting Wang
RWada
马春旺;彭丹;魏慧玲;牛中明;王玉廷;RWada(Institute of Particle and Nuclear Physics,Henan Normal University,Xinxiang 453007,China;School of Physics,Henan Normal University,Xinxiang 453007,China;School of Physics and Materials Science,Anhui University,Hefei 230601,China;Institute of Cyclotron,Texas A&M Univ,College Stn,TX 77843,USA)
基金
Supported by the National Natural Science Foundation of China(11975091,U1732135,11875070)
Natural Science Foundation of Henan Province(162300410179)
supported by the US Department of Energy(DE-FG02-93ER40773)
