• Chinese Physics C
  • Vol. 44, Issue 1, (2020)
Chun-Wang Ma1、2、*, Dan Peng1, Hui-Ling Wei1, Zhong-Ming Niu1, Yu-Ting Wang1, and R. Wada1
Author Affiliations
  • 1Institute of Cyclotron, Texas A&M Univ4Institute of Cyclotron, Texas A&M Univ, College Stn, TX 77843, USA
  • 1Institute of Particle and Nuclear Physics, Henan Normal University1Institute of Particle and Nuclear Physics, Henan Normal University, Xinxiang 453007, China
  • 1School of Physics and Materials Science, Anhui University3School of Physics and Materials Science, Anhui University, Hefei 230601, China
  • 1School of Physics, Henan Normal University2School of Physics, Henan Normal University, Xinxiang 453007, China
  • 2School of Physics, Henan Normal University2School of Physics, Henan Normal University, Xinxiang 453007, China
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    DOI: 10.1088/1674-1137/44/1/014104 Cite this Article
    Chun-Wang Ma, Dan Peng, Hui-Ling Wei, Zhong-Ming Niu, Yu-Ting Wang, R. Wada. Isotopic cross-sections in proton induced spallation reactions based on the Bayesian neural network method *[J]. Chinese Physics C, 2020, 44(1): Copy Citation Text show less

    Abstract

    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.
    Chun-Wang Ma, Dan Peng, Hui-Ling Wei, Zhong-Ming Niu, Yu-Ting Wang, R. Wada. Isotopic cross-sections in proton induced spallation reactions based on the Bayesian neural network method *[J]. Chinese Physics C, 2020, 44(1):
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