Journal
CHINESE PHYSICS C
Volume 44, Issue 1, Pages -Publisher
IOP PUBLISHING LTD
DOI: 10.1088/1674-1137/44/1/014104
Keywords
BNN method; spallation reaction; p plus A; SPACS parametrization; cross-section prediction
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Funding
- National Natural Science Foundation of China [11975091, U1732135, 11875070]
- Natural Science Foundation of Henan Province [162300410179]
- US Department of Energy [DE-FG02-93ER40773]
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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.
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