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

Abstract

In gamma-ray spectroscopy, a number of neutrons are emitted from the nuclei together with the gamma-rays 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.

10 pages, 8 figures

References in corpus (1)

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