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arXiv · 2507.06370

New approach for the quantification of uncertainties in reaction modeling via data-driven multi-objective optimization

N. Dimitrakopoulos·G. Perdikakis·F. Montes·P. Gastis·S. A. Kuvin·H. Y. Lee·P. Tsintari·A. V. Voinov
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Abstract

We introduce a new multi-objective optimization approach to determine uncertainty-quantified nuclear reaction parameters in the Hauser-Feshbach framework. By simultaneously accounting for all available data across multiple reaction channels we capture parameter correlations and estimate data-driven uncertainties. We implement in the Ni-Ge region yielding uncertainty-quantified model parameters for both stable and unstable isotopes. We estimate resonance spacings for nuclei beyond experimental reach and validate our method by calculating a known cross-section outside our optimization region.

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N. Dimitrakopoulos, G. Perdikakis, F. Montes, P. Gastis, S. A. Kuvin, H. Y. Lee, P. Tsintari, A. V. Voinov. 2025-07-08. New approach for the quantification of uncertainties in reaction modeling via data-driven multi-objective optimization. https://arxiv.org/abs/2507.06370

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