1207.1561 (Serkan Akkoyun)

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

Serkan Akkoyun

The gamma-ray tracking detector arrays, such as advanced gamma ray tracking array (AGATA), are quite powerful detection systems in nuclear structure physic studies. In these arrays, the sequences of the gamma-ray interaction points in the detectors can correctly be identified in order to obtain true gamma-ray energies emitted from the nuclei of interest. Together with the gamma-rays, a number of neutrons are also emitted from the nuclei and these neutrons influence gamma-ray spectra. An obvious method of separating between neutrons and gamma-rays is based on the time-of-flight (tof) technique. This work aims obtaining tof distributions of gamma-rays and neutrons by using feed-forward artificial neural network (ANN). It was shown that, ANN can correctly classify gamma-ray and neutron events. Testing of trained networks on experimental data clearly shows up tof discrimination of gamma-rays and neutrons.

View original: http://arxiv.org/abs/1207.1561