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

Creative Commons License

Akkoyun S.

ANNALS OF NUCLEAR ENERGY, vol.55, pp.297-301, 2013 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 55
  • Publication Date: 2013
  • Doi Number: 10.1016/j.anucene.2013.01.006
  • Title of Journal : ANNALS OF NUCLEAR ENERGY
  • Page Numbers: pp.297-301


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.