Title
Improvement studies on neutron-gamma separation in HPGe detectors by using neural networks
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 were previously determined for separation between 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 obtained from 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 0.50.
Year
DOI
Venue
2013
10.17776/csj.30825
Cumhuriyet Science Journal
Keywords
Field
DocType
artificial neural network
Neutron,Spectral line,Beam (structure),Nuclear physics,Nuclear reaction,Detector,Ion,Semiconductor detector,Radiant energy,Physics
Journal
Volume
Issue
ISSN
abs/1304.3209
1
Cumhuriyet Science Journal, 34-1 (2013) 42
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Serkan Akkoyun100.34
Tuncay Bayram200.34
S. Okan Kara300.34