Bayesian approach to energy dependence of fission product yields of ²³⁵U by data augmentation

References

• Hahn O, Strassmann F. Über den Nachweis und das Verhalten der bei der Bestrahlung des Urans mittels Neutronen entstehenden Erdalkalimetalle. Naturwissenschaften. 1939;27(1):11–15.
   Google Scholar
• Chadwick M, Herman M, Obložinský P, et al. ENDF/B-VII. 1 Nuclear data for science and technology: cross sections, covariances, fission product yields and decay data. Nucl Data Sheets. 2011;112(12):2887–2996. Special Issue on ENDF/B-VII. 1 Library; Available from: https://www. sciencedirect.com/science/article/pii/S009037521100113X10.1016/j.nds.2011.11.002
   Google Scholar
• Furutaka K, Harada H, Nakamura S, et al. Cross section of thermal-neutron capture reaction by 99Tc. J Nucl Radiochem Sci. 2005;6(3):283–286. Available from: https://cir.nii.ac.jp/crid/1390282679457496448. 10.14494/jnrs2000.6.3_283
   Google Scholar
• Chadwick M, Kawano T, Barr D, et al. Fission product yields from fission spectrum n+239Pu${\rm{n}} + { ^{239}}{\rm{Pu}}$ for ENDF/B-VII.1. Nucl Data Sheets. 2010;111(12):2923–2964. Nuclear Reaction Data; Available from: https://www.sciencedirect.com/science/article/pii/S009037521000102X
   Google Scholar
• Iwamoto O, Iwamoto N, Kunieda S, et al. Japanese evaluated nuclear data library version 5: JENDL-5. J Nucl Sci Technol. 2023;60(1):1–60. Available from: https://doi.org/10.1080/00223131.2022.2141903
   Web of Science ®Google Scholar
• Brown D, Chadwick M, Capote R, et al. ENDF/B-VIII.0: The 8th major release of the nuclear reaction data library with CIELO-project cross sections, new standards and thermal scattering data. Nucl Data Sheets. 2018;148:1–142. Special Issue on Nuclear Reaction Data; Available from: https://www.sciencedirect.com/science/article/pii/S009037521830020610.1016/j.nds.2018.02.001
   Google Scholar
• Plompenand AJM, Cabellos O, De Saint Jean C, et al. The joint evaluated fission and fusion nuclear data library, JEFF-3.3. Eur Phys J A. 2020;56:181. Available from: https://rdcu.be/b5CJV 7 10.1140/epja/s10050-020-00141-9
   Web of Science ®Google Scholar
• Tonchev AP, Silano JA, Hagmann C H, Stoyer, Mark A, Gooden, Matthew, et al. Toward shortlived and energy-dependent fission product yields from neutron-induced fission. EPJ Web Conf. 2020;239:03001. Available from: https://doi.org/10.1051/epjconf/202023903001
   Google Scholar
• Gooden M, Arnold C, Becker J, et al. Energy dependence of fission product yields from 235U,238U${ ^{235}}{\rm{U}},{ ^{238}}{\rm{U}}$ and 239Pu${ ^{239}}{\rm{Pu}}$ for incident neutron energies between 0.5 and 14.8MeV$14.8{\rm{MeV}}$. Nucl Data Sheets. 2016;131:319356. Special Issue on Nuclear Reaction Data; Available from: https://www.sciencedirect.com/science/article/pii/S009037521500071X.
   Google Scholar
• Bhatia C, Fallin BF, Gooden ME, et al. Exploratory study of fission product yields of neutroninduced fission of 235U,238U${ ^{235}}{\rm{U}},{ ^{238}}{\rm{U}}$, and 239Pu${ ^{239}}{\rm{Pu}}$ at 8.9MeV$8.9{\rm{MeV}}$. Phys Rev C. 2015 Jun;91:064604. Available from: https://link.aps.org/do i/10.1103/PhysRevC.91.064604
   Google Scholar
• Bulgac A. New developments in fission studies within the time-dependent density functional theory framework. In: 15th International Conference on Nuclear Data for Science and Technology; 10; 2022.
   Google Scholar
• Bulgac A, Magierski P, Roche KJ, et al. Induced fission of 240Pu${ ^{240}}{\rm{Pu}}$ within a real-time microscopic framework. Phys Rev Lett. 2016 Mar;116:122504. Available from: 10.1103/PhysRevLett.116.122504
   PubMed Web of Science ®Google Scholar
• Younes W, Berger JF. A microscopic theory of fission dynamics based on the generator coordinate method preface. Switzerland: Springer; 2019. NUCLEAR PHYSICS AND RADIATION PHYSICS; Available from: http://inis.iaea.org/search/search.aspx?orig_q=RN: 52120026
   Google Scholar
• Okumura S, Kawano T, Jaffke P, et al. 235U(n,f)${ ^{235}}{\rm{U}}\left({{\rm{n}},{\rm{f}}} \right)$ Independent fission product yield and isomeric ratio calculated with the statistical Hauser-Feshbach theory. J Nucl Sci Technol. 2018;55(9):1009–1023. Available from: https://doi.org/10.1080/00223131.2018.1467288
   Web of Science ®Google Scholar
• Ishizuka C, Usang MD, Ivanyuk FA, et al. Four-dimensional Langevin approach to low-energy nuclear fission of 236${ ^{236}}$ U. Phys Rev C. 2017 Dec;96:064616. Available from: https://link.aps.org/doi/10. 1103/PhysRevC.96.064616.
   Web of Science ®Google Scholar
• Neal RM. Bayesian learning for neural networks, lecture notes in statistics. Springer New York, NY; 1995.
   Google Scholar
• Izmailov P, Vikram S, Hoffman MD, et al. What are bayesian neural network posteriors really like? In: Proceedings of the 38th International Conference on Machine Learning; Vol. 139; 2021. p. 4629–4640. Available from: https://proceedings.mlr.press/v139/izmailov21a.html
   Google Scholar
• Jang H, Lee J. Generative Bayesian neural network model for risk-neutral pricing of American index options. Quantitative Finance. 2019;19(4):587–603. Available from: 10.1080/14697688.2018.1490807.
   Web of Science ®Google Scholar
• Yang W, Lorch L, Graule MA, et al. Incorporating interpretable output constraints in Bayesian neural networks. In: Adv Neural Inf Process Syst; 2020. Available from: https://arxiv.org/abs/2010.10969
   Google Scholar
• Niu Z, Liang H Nuclear mass predictions based on Bayesian neural network approach with pairing and shell effects. Phys Lett B. 2018;778:48–53. Available from: https://www.sciencedirect.com/science/article/pii/S0370269318300091.10.1016/j.physletb.2018.01.002
   Web of Science ®Google Scholar
• Utama R, Piekarewicz J, Prosper HB. Nuclear mass predictions for the crustal composition of neutron stars: A Bayesian neural network approach. Phys Rev C. 2016 Jan;93:014311. Available from: https ://link.aps.org/ 10.1103/PhysRevC.93.014311
   Web of Science ®Google Scholar
• Talou P, Young P, Kawano T, et al. Quantification of uncertainties for evaluated neutron-induced reactions on actinides in the fast energy range. Nucl Data Sheets. 2011;112(12):3054–3074. Spe-cial Issue on ENDF/B-VII. 1 Library; Available from: https://www.sciencedirect.com/science/article/pii/S0090375211001165.
   Google Scholar
• Wang ZA, Pei JC, Chen YJ, et al. Bayesian approach to heterogeneous data fusion of imperfect fission yields for augmented evaluations. Phys Rev C. 2022 Aug;106:L021304. Available from: https://link.aps.org/do i/10.1103/PhysRevC.106.L021304
   Web of Science ®Google Scholar
• Wang ZA, Pei J, Liu Y, et al. Bayesian evaluation of incomplete fission yields. Phys Rev Lett. 2019 Sep;123:122501. Available from: https://link.aps.org/do i/10.1103/PhysRevLett.123.122501
   PubMed Web of Science ®Google Scholar
• Wang ZA, Pei J. Optimizing multilayer Bayesian neural networks for evaluation of fission yields. Phys Rev C. 2021 Dec;104:064608. Available from: https://link.aps.org/do i/10.1103/PhysRevC. 104.064608.
   Web of Science ®Google Scholar
• Brosa U, Grossmann S, Müller A Nuclear scission. Phys Rep. 1990;197(4):167–262. Available from: https://www.sciencedirect.com/science/article/pii/037015739090114H. 10.1016/0370-1573(90)90114-H
   Web of Science ®Google Scholar
• Bishop, Christopher M. Pattern recognition and machine learning (Information Science and Statistics). Berlin, Heidelberg: Springer-Verlag; 2006. Chapter 1, 3, 5.
   Google Scholar
• Brooks S, Gelman A, Jones G, et al., editors. Handbook of Markov Chain Monte Carlo. Chapman and Hall/CRC; 2011. Available from: 1 0.1201%2Fb10905
   Google Scholar
• Hoffman MD, Gelman A, et al. The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. J Mach Learn Res. 2014;15(1):1593–1623.
   Google Scholar
• Bingham E, Chen JP, Jankowiak M, et al. Pyro: Deep universal probabilistic programming. J Mach Learn Res. 2019;20:28. Available from: http://jmlr.org/papers/v20/18-403.html
   Google Scholar
• Naik H, Mulik V, Prajapati P, et al. Masrs distribution in the quasi-mono-energetic neutron-induced fission of 238${ ^{238}}$ U. Nucl Phys A. 2013;913:185–205. Available from: https ://www. sciencedirect.com/science/article/pii/S0375947413005861.
   Web of Science ®Google Scholar
• Naik H, Mukerji S, Crasta R, et al. Measurement of fission product yields in the quasi-monoenergetic neutron-induced fission of 238U${ ^{238}}{\rm{U}}$. Nucl Phys A. 2015;941:16–37. Available from: https://www.sciencedirect.com/science/article/pii/S0375947415001244
   Web of Science ®Google Scholar
• Katakura JI. A systematics of fission product mass yields with 5 Gaussian functions. Chiba: Japan At. Energy Res. Inst.; 2003. Available from: http://cds.cern.ch/record/747584
   Google Scholar