Retroactive Generation of Covariance Matrix of Nuclear Model Parameters Using Marginalization Techniques

Abstract An uncertainty propagation methodology relying on marginalization techniques was recently developed to produce covariance matrices between existing model parameters involved in describing neutron-induced reactions. This work has been implemented in the nuclear data assimilation tool CONRAD. The performance of the code was demonstrated through simplified test cases based on a Reich-Moore description of the 155Gd(n,γ) reaction. Results are compared with those produced via Monte Carlo techniques.