Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks

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Cumhuriyet Üniversitesi Fen-Edebiyat Fakültesi Fen Bilimleri Dergisi
Volume:34 Issue:1
Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks

Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks

Authors : Serkan AKKOYUN, Tuncay BAYRAM, Seyit KARA

Pages : 42-51

View : 48 | Download : 18

Publication Date : 2013-04-29

Article Type : Research Paper

Abstract :The neutrons emitted in heavy-ion fusion-evaporation (HIFE) reactions together with the gamma-rays cause unwanted backgrounds in gamma-ray spectra. Especially in the nuclear reactions where relativistic ion beams (RIBs) are used, these neutrons are serious problem. They have to be rejected in order to obtain clearer gamma-ray peaks. In this study, the radiation energy and three criteria which are previously determined for separation of neutron and gamma-rays in the HPGe detectors have been used in artificial neural network (ANN) for improving of the decomposition power. According to the preliminary results, by the help of ANN method, the ratio of neutron rejection has been improved by a factor of 1.27 and the ratio of the lost in gamma-rays has been decreased by a factor of 0.5.
Keywords : HPGe detectors, gamma ray tracking, artificial neural network, Geant4, neutron gamma separation

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