Nuclear mass systematics by complementing the Finite Range Droplet Model with neural networks

Details Nuclear mass systematics by complementing the Finite Range Droplet Model with neural networks Nuclear mass systematics by complementing the Finite Range Droplet Model with neural networks

2005-11-30

arxiv.org/abs/nucl-th/0511088v1

Physics

Nuclear Physics

Nuclear Theory

Proceedings for the 15th Hellenic Symposium on Nuclear Physics

Scientific paper

A neural-network model is developed to reproduce the differences between experimental nuclear mass-excess values and the theoretical values given by the Finite Range Droplet Model. The results point to the existence of subtle regularities of nuclear structure not yet contained in the best microscopic/phenomenological models of atomic masses. Combining the FRDM and the neural-network model, we create a hybrid model with improved predictive performance on nuclear-mass systematics and related quantities.

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