Time-of-flight discrimination between gamma-rays and neutrons by using artificial neural networks

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Akkoyun S.

ANNALS OF NUCLEAR ENERGY, cilt.55, ss.297-301, 2013 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 55
  • Basım Tarihi: 2013
  • Doi Numarası: 10.1016/j.anucene.2013.01.006
  • Dergi Adı: ANNALS OF NUCLEAR ENERGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.297-301
  • Anahtar Kelimeler: Artificial neural network, Time-of-flight, Monte Carlo simulation, HPGe detector, PHYSICAL FORMULA CONSTRUCTION, AGATA
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

In gamma-ray spectroscopy, a number of neutrons are emitted from the nuclei together with the gamma-rays. These neutrons influence gamma-ray spectra. An obvious method for discrimination between neutrons and gamma-rays is based on the time-of-flight (tot) technique. In this work, the tof distributions of gamma-rays and neutrons were obtained both experimentally and by using artificial neural networks (ANNs). It was shown that, ANN can correctly classify gamma-ray and neutron events. Also, for highly nonlinear detector response for tof, we have constructed consistent empirical physical formulas (EPFs) by appropriate ANNs. These ANN-EPFs can be used to derive further physical functions which could be relevant to discrimination between gamma-rays and neutrons. (C) 2013 Elsevier Ltd. All rights reserved.