Wednesday·June 12, 2019

[Submitted on 11 Jun 2019]

Bayesian Evaluation of Incomplete Fission Yields

Zi-Ao wang · Junchen Pei · Yue Liu · Yu Qiang

Fission product yields are key infrastructure data for nuclear applications in many aspects. It is a challenge both experimentally and theoretically to obtain accurate and complete energy-dependent fission yields. We apply the Bayesian neural network (BNN) approach to learn existed fission yields and predict unknowns with uncertainty quantification. We demonstrated that BNN is particularly useful for evaluations of fission yields when incomplete experimental data are available. The BNN results are quite satisfactory on distribution positions and energy dependencies of fission yields.