Adjustment of non-linear interaction parameters for relativistic mean field approach by using artificial neural networks
Yazarlar (3)
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Özgün Makale
(SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale)
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| Dergi Adı | Physics of Atomic Nuclei (Q4) | ||
| Dergi ISSN | 1063-7788 Dergi Bilgileri (2018) | ||
| Makale Dili | – | Basım Tarihi | 01-2018 |
| Kabul Tarihi | – | Yayınlanma Tarihi | 01-05-2018 |
| Cilt / Sayı / Sayfa | 81 / 3 / 288–295 | DOI | 10.1134/S1063778818030043 |
| Makale Linki | https://link.springer.com/article/10.1134/S1063778818030043 | ||
| UAK Araştırma Alanları |
Dedektör Teknolojisi
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| Özet |
| The relativistic mean field (RMF) model with a small number of adjusted parameters has been used successfully in the last thirty years for predictions of various ground-state nuclear properties of nuclei. In this model, Dirac and Klein–Gordon like equations obtained from application of variation principle on phenomenological Lagrangian density are solved iteratively for calculations of nuclear properties of nuclei. For this purpose, parameters such as masses of considered mesons, nucleon–meson coupling constants, and self-couplings of mesons are needed and they are fitted from experimental data. Some parameter sets for RMF model introduced to correct predictions of nuclear properties of nuclei cover nuclidic chart. Besides Artificial Neural Network (ANN) method is used successfully in many field of science as in nuclear physics. ANN is known as a very powerful tool that are used when standard techniques fail … |
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| Google Scholar | 11 |