The Physics Society of Iran Iranian Journal of Physics Research 1682-6957 18 2 2019 11 26 Determination of saturation depth in Compton scattering using Artificial Neural Network Determination of saturation depth in Compton scattering using Artificial Neural Network 195 205 1349 10.29252/ijpr.18.2.195 FA S Ashrafi D Alizadeh O Jahanbakhsh Journal Article 2019 11 26 Abstract: The intensity of Compton scattered γ-ray photons provide useful information about the electron density distribution of a test sample. Because of photon attenuation, the application of this method is limited to a certain depth of the sample (saturation depth). The saturation depth value depends on the energy and intensity of primary photons and on the material of the sample. In this study, we measured the energy spectrum of the scattered photons of 662 keV at 90° with a NaI(Tl) scintillator; and determined the saturation depth of the sample by the Artificial Neural Network (ANN) algorithm. Two sets of samples with known and unknown density were used to train and test the network, respectively. The highest precision (with 0.15% relative error) was achieved by using the Levenbert-Marquardt algorithm with five hidden layers. Abstract: The intensity of Compton scattered γ-ray photons provide useful information about the electron density distribution of a test sample. Because of photon attenuation, the application of this method is limited to a certain depth of the sample (saturation depth). The saturation depth value depends on the energy and intensity of primary photons and on the material of the sample. In this study, we measured the energy spectrum of the scattered photons of 662 keV at 90° with a NaI(Tl) scintillator; and determined the saturation depth of the sample by the Artificial Neural Network (ANN) algorithm. Two sets of samples with known and unknown density were used to train and test the network, respectively. The highest precision (with 0.15% relative error) was achieved by using the Levenbert-Marquardt algorithm with five hidden layers. https://ijpr.iut.ac.ir/article_1349_bcc0d400288793e8bdcd7c19a8ac0c2b.pdf