Generation of nuclear data using Gaussian process regression

Iwamoto, Hiroki  

We present a new approach to generate nuclear data from experimental cross section data by Gaussian process regression. This paper focuses on generating proton-induced nuclide production cross sections for nickel target. Our results provide reasonable fitting curves together with their uncertainties and suggest that this approach appears to be effective in generating or evaluating the nuclear data. Besides, our results suggest that our approach could be available for experimental design in terms of reducing the generated nuclear data uncertainty.