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arXiv · 2508.19474

Reducing parametric uncertainties through information geometry methods

M. Imbrišak·A. E. Lovell·M. R. Mumpower
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Abstract

Information geometry is a study of applying differential geometry methods to challenging statistical problems, such as uncertainty quantification. In this work, we use information geometry to study how measurement uncertainties in pre-neutron emission mass distributions affect the parameter estimation in the Hauser-Feshbach fission fragment decay code, CGMF. We quantify the impact of reduced uncertainties on the pre-neutron mass yield of specific masses to these parameters, for spontaneous fission of ${}^{252}$Cf, first using a toy model assuming Poissonian uncertainties, then an experimental measurement taken from Göök et al., 2014 in EXFOR. We achieved a reduction of up to $\sim15\%$ in CGMF parameter errors, predominantly in $w_0^{(1)}$ and $w_1^{(0)}$.

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M. Imbrišak, A. E. Lovell, M. R. Mumpower. 2025-09-12. Reducing parametric uncertainties through information geometry methods. https://arxiv.org/abs/2508.19474

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