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arXiv · 1301.2407

Systematics on ground-state energies of nuclei within the neural networks

Tuncay Bayram·Serkan Akkoyun·S. Okan Kara
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Abstract

One of the fundamental ground-state properties of nuclei is binding energy. In this study, we have employed artificial neural networks (ANNs) to obtain binding energies based on the data calculated from Hartree-Fock-Bogolibov (HFB) method with the two SLy4 and SKP Skyrme forces. Also, ANNs have been employed to obtain two-neutron and two-proton separation energies of nuclei. Statistical modeling of nuclear data using ANNs has been seen as to be successful in this study. Such a statistical model can be possible tool for searching in systematics of nuclei beyond existing experimental nuclear data.

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Tuncay Bayram, Serkan Akkoyun, S. Okan Kara. 2013-01-11. Systematics on ground-state energies of nuclei within the neural networks. https://doi.org/10.1016/j.anucene.2013.07.039

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