Maximization of representativity factors for experimental planning of cross-section measurements: An information theoretic approach

The similarity between two nuclear systems is expressed by the representativity factors and maximizing its value to unity reduces the uncertainty from its existing value. As the representativity factor is a function of covariance matrix of neutron cross-sections, the inherent systematic uncertainty in neutron cross-sections inhibits it from approaching unity and hence statistical procedures have to be resorted to minimize the systematic uncertainty. As the conventional statistical techniques fail when systematic uncertainty is dominant, we propose an entropy based information theoretic approach of maximizing the mutual information by the knowledge of bounds for the correlated elements. We show that maximizing the mutual information and the representativity factors express the similar phenomena of uncertainty reduction. We estimated the bounds for the correlated elements of the correlation matrix for minor actinides and show how the systematic uncertainty is reduced when lower bound values are considered. These lower bound values aid in experimental planning for future measurement of cross-sections with reduced systematic uncertainty.