Friday, February 17, 2012

1202.3532 (Serkan Akkoyun et al.)

Consistent empirical physical formula construction for recoil energy
distribution in HPGe detectors using artificial neural networks
   [PDF]

Serkan Akkoyun, Nihat Yildiz
The gamma-ray tracking technique is one of the highly efficient detection
method in experimental nuclear structure physics. On the basis of this method,
two gamma-ray tracking arrays, AGATA in Europe and GRETA in the USA, are
currently being developed. The interactions of neutrons in these detectors lead
to an unwanted background in the gamma-ray spectra. Thus, the interaction
points of neutrons in these detectors have to be determined in the gamma-ray
tracking process in order to improve photo-peak efficiencies and peak-to-total
ratios of the gamma-ray peaks. Therefore, the recoil energy distributions of
germanium nuclei due to inelastic scatterings of 1-5 MeV neutrons were obtained
both experimentally and using artificial neural networks. Also, for highly
nonlinear detector response for recoiling germanium nuclei, we have constructed
consistent empirical physical formulas (EPFs) by appropriate layered
feed-forward neural networks (LFNNs). These LFNN-EPFs can be used to derive
further physical functions which could be relevant to determination of neutron
interactions in gamma-ray tracking process.
View original: http://arxiv.org/abs/1202.3532

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