G-HyND: a hybrid nuclear data estimator with Gaussian processes

References

• Shibata K, Iwamoto O, Nakagawa T, et al. JENDL-4.0: a new library for nuclear science and engineering. J Nucl Sci Technol. 2011 Jan;48:1–30.
   Web of Science ®Google Scholar
• Brown DA, Chadwick MB, 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.
   Google Scholar
• Koning AJ, Koning E, Dean J, et al. Status of the nuclear JEFF nuclear data library. J Korean Phys Soc. 2011 Aug;59:1057–1062.
   Web of Science ®Google Scholar
• Stankovskiy A, Iwamoto H, Çelik Y, et al. High-energy nuclear data uncertainties propagated to MYRRHA safety parameters. Ann Nucl Energy. 2018 Oct;120:207–218.
   Web of Science ®Google Scholar
• Iwamoto H, Meigo S, Matsuda H. A comprehensive study of spallation models for proton-inducded spallation product yields utilized in transport calculation. EPJ Web of Conference. 2020 Sep;239:06001.
   Google Scholar
• Iwamoto O. Development of a comprehensive code for nuclear data evaluation, CCONE, and validation using neutron-induced cross-sections for uranium isotopes. J Nucl Sci Technol. 2007 May;44:687–697.
   Web of Science ®Google Scholar
• Herman M, Capote R, Carlson BV, et al. EMPIRE: nuclear reaction model code system for data evaluation. Nucl Data Sheets. 2007 Dec;108:2655–2715.
   Google Scholar
• Koning AJ, Rochman D. Modern nuclear data evaluation with the TALYS code system. Nucl Data Sheets. 2012 Dec;113:2841–2934.
   Google Scholar
• Cugnon J, Volant C, Vuillier S. Improved intranuclear cascade model for nucleon-nucleus interactions. Nucl Phys A. 1997 Jul;620(4):475–509.
   Web of Science ®Google Scholar
• Niita K, Chiba S, Maruyama T, et al. Analsysis of the (N, xN´) reactions by quantum molecular dynamics plus statistical decay model. Phys Rev C. 1995 Nov;52:2620–2635.
   PubMed Web of Science ®Google Scholar
• Ono A, Horiuchi H, Maruyama T, et al. Antisymmetrized version of molecular dynamics with two-nucleon collisions and its application to heavy ion reactions. Prog Theor Phys. 1992 May;87(5):1185–1206.
   Google Scholar
• Rasmussen CE, Williams CKI. Gaussian processes for machine learning. Cambridge: the MIT Press; 2006.
   Google Scholar
• Schnabel G, Sjöstrand H, Hansson J, et al. Conception and software implementation of a nuclear data evaluation pipeline. Nucl Data Sheets. 2021 May;173:239–284.
   Google Scholar
• Schnabel G, Leeb H. Differential cross-sections and the impact of model defects in nuclear data evaluation. EPJ Web of Conf. 2016 Mar;111:09001.
   Google Scholar
• Schnabel G, De Saint Jean C. Estimating model bias over the complete nuclide chart with sparce Gaussian processes at the example of INCL/ABLA and double-differential neutron spectra. EPJ Nucl Sci Technol. 2018 Nov;4:33.
   Web of Science ®Google Scholar
• Helgesson P, Sjöstrand H. Treating model defects by fitting smoothly varying model parameters: energy dependence in nuclear data evaluation. Ann Nucl Energy. 2018 May;120:35–47.
   Web of Science ®Google Scholar
• Iwamoto H. Generation of nuclear data using Gaussian process regression. J Nucl Sci Technol. 2020 Aug;57:932–938.
   Web of Science ®Google Scholar
• Poenitz WP and Aumeier SE. The simultaneous evaluation of the standards and other cross-sections of importance for technology. USA: Argonne National Laboratory; 1997. ANL/NDM-139.
   Google Scholar
• Kawano T, Matsunobu H, Murata T, et al. Evaluation of fission cross sections and covariances for 233U, 235U, 238U, 239Pu, 240Pu, and 241Pu Japan: Japan Atomic Energy Research Institute. JAERI-Research 2000-004. 2000.
   Google Scholar
• Scipy.org: optimization and root finding (scipy.optimize) [Internet]. [ cited 2021 Jun 2]. Available from: https://docs.scipy.org/doc/scipy/reference/optimize.html
   Google Scholar
• Nocedal J, Write S. Numerical optimization. New York: Springer; 2006.
   Google Scholar
• Zhu C, Byrd RH, Nocedal J. L-BFGS-B: algorithm 778: l-BFGS-B, FORTRAN routines for large scale boud constrained optimization. ACM Trans Math Soft. 1997;23(4):550–560.
   Web of Science ®Google Scholar
• Kunieda S, Iwamoto O, Iwamoto N, et al. Overview of JENDL-4.0/HE and benchmark calculations. In Proceedings of the 2015 Symposium on Nuclear Data; 2015 Nov 19–20; Tokai (Japan): Ibaraki Quantum Beam Research Center; 2016.
   Google Scholar
• Boudard A, Cugnon J, David JC, et al. New potentialities of the Liège intranuclear cascade model for reactions induced by nucleons and light charged particles. Phys Rev C. 2013;87:014606.
   Web of Science ®Google Scholar
• Furihata S. Statistical analysis of light fragment production from medium energy proton-induced reactions. Nucl Instrum Meth B. 2000 Nov;171:251–258.
   Web of Science ®Google Scholar
• Sato T, Iwamoto Y, Hashimoto S, et al. Features of particle and heavy ion transport code system (PHITS) version 3.02. J Nucl Sci Technol. 2018 Jun;55:529–533.
   Web of Science ®Google Scholar
• Otuka N, Dupont E, Semkova V, et al. Towards a more complete and accurate experimental nuclewar reaction data library (EXFOR): international collaboration between nuclear reaction data centres (NRDC). Nucl Data Sheets. 2014 Jun;20:272–276.
   Google Scholar
• Kawano T. DeCE: the ENDF-6 data interface and nuclear data evaluation assist code. J Nucl Sci Technol. 2019 Nov;56:1029–1035.
   Web of Science ®Google Scholar
• Koning AJ and Rochman D. EXFORTABLES-1.0. IAEA NDS document series IAEA(NDS)-235 [Internet]. 2020 Dec [cited 2021 Jun 2]. Available from: https://nds.iaea.org/publications/iada-nds/iaea-nds-0235.pdf
   Google Scholar
• Cugnon J, L’Hôte D, Vandermeulen J. Simple parametrization of cross-sections for nuclear transport studies up to the GeV range. Nucl Instrum Meth B. 1996 May;111:215–220.
   Web of Science ®Google Scholar
• Niita K, Takada H, Meigo S, et al. High-energy particle transport code NMTC/JAM. Nucl Instrum Meth B. 2000 Nov;184:406–420.
   Web of Science ®Google Scholar
• Sato T, Kataoka R, Yasuda H, et al. Air shower simulation for WASAVIES: warning system for aviation exposure to solar energetic particles. Radiat Prot Dosim. 2014;161:274–278.
   Web of Science ®Google Scholar
• Watanabe Y, Kosako K, Kunieda S, et al. Status of JENDL high energy file. J Korean Phys Soc. 2011 Aug;59:1040–1045.
   Web of Science ®Google Scholar
• Capote R, Badikov S, Carlson AD, et al. Unrecognized source of uncertainties (USU) in experimental nuclear data. Nucl Data Sheets. 2020 Jan;163:191–227.
   Google Scholar
• Kawano T, Hanson M, Frankle P, et al. Evaluation and propagation of the 239Pu fission cross-section uncertainties using a Monte Carlo technique. Nucl Sci Eng. 2006;153:1–7.
   Web of Science ®Google Scholar
• Iwamoto H, Stankovskiy A, Fiorito L, et al. Monte Carlo uncertainty quantification of the effective delayed neutron fraction. J Nucl Sci Technol. 2018 May;55:539–547.
   Web of Science ®Google Scholar
• Iwamoto H, Meigo S. Estimation of uncertainty in lead spallation particle multiplicity and its propagation to a neutron energy spectrum. J Nucl Sci Technol. 2020 Mar;57:276–290.
   Web of Science ®Google Scholar