Estimations of beta-decay energies through the nuclidic chart by using neural network

AKKOYUN S., Bayram T., Turker T.

RADIATION PHYSICS AND CHEMISTRY, cilt.96, ss.186-189, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 96
  • Basım Tarihi: 2014
  • Doi Numarası: 10.1016/j.radphyschem.2013.10.002
  • Dergi Adı: RADIATION PHYSICS AND CHEMISTRY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.186-189
  • Anahtar Kelimeler: Beta decay energy, Hartree-Fock-BCS method, Artificial neural network, Nuclear mass, IMPACT PARAMETER DETERMINATION
  • Karadeniz Teknik Üniversitesi Adresli: Hayır

Özet

One of the main characteristics of unstable nuclei is beta-decay energy (Q(beta)). It is determined by different methods such as beta endpoint measurements, counting in coincidence with annihilation radiation, electron capture (EC)/beta(+) ratio method, method of gamma absorption with X-ray coincidence. Beta-decay energy is a roughly linear function of atomic and mass numbers. Due to the fact that artificial neural network (ANN) is sufficient for nonlinear function approximation, in this study by using the nuclear masses from Hartree-Fock-BCS method, Q(beta) values have been obtained by ANN. It is seen that the estimations of the ANN are consistent with the calculated data within some deviation. (C) 2013 Elsevier Ltd. All rights reserved.

One of the main characteristics of unstable nuclei is beta-decay energy (Qβ). It is determined by different methods such as beta endpoint measurements, counting in coincidence with annihilation radiation, electron capture (EC)/β+ ratio method, method of gamma absorption with X-ray coincidence. Beta-decay energy is a roughly linear function of atomic and mass numbers. Due to the fact that artificial neural network (ANN) is sufficient for nonlinear function approximation, in this study by using the nuclear masses from Hartree–Fock–BCS method, Qβ values have been obtained by ANN. It is seen that the estimations of the ANN are consistent with the calculated data within some deviation.