A study on ground-state energies of nuclei by using neural networks
Küçük Resim Yok
Tarih
2014
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
PERGAMON-ELSEVIER SCIENCE LTD
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
One of the fundamental ground-state properties of nuclei is binding energy. Artificial neural networks (ANN) have been performed to obtain binding energies of nuclei based on the data calculated from Hartree-Fock-Bogolibov method with two Skyrme forces SLy4 and SKP. ANN has been employed to obtain two-neutron and two-proton separation energies of nuclei. Statistical modeling of ground-state energies using ANN has been seen as to be successful in this study. Particularly, predictive power of ANN has been drawn from estimations for energies of Sr, Xe, Er and Pb isotopic chains which are not seen before by the network. The study shows that such a statistical model can be possible tool for searching in systematic of nuclei beyond existing experimental data. (C) 2013 Elsevier Ltd. All rights reserved.
Açıklama
Anahtar Kelimeler
Ground-state energies, Artificial neural network, Hartree-Fock-Bogoliubov method
Kaynak
ANNALS OF NUCLEAR ENERGY
WoS Q Değeri
Q3
Scopus Q Değeri
Q1
Cilt
63
