Inference and visualization of nuclear magnetic moment studies with neuro-fuzzy systems

Abstract

This study aims to predict the magnetic moments of nuclei with odd-A numbers in a certain region of which magnetic moment has not yet been calculated, using the Adaptive Neuro-Fuzzy Inference System (Anfis) method. In our Anfis model, the proton number (Z), neutron number (N), and spin value (I) are used as inputs for nuclei with 1≤Z≤88. With these input data, 526 odd-A nuclei are trained, and 124 nuclei are tested. The fact that the Anfis model was closer to the experimental data in the training and testing processes than the theoretical methods encouraged us to make inferences about the nuclei of which experimental nuclear magnetic moment is unknown. To that end, inferences have been made for 165 nuclei without experimental magnetic moments in regions 1≤Z≤28. In this region, Na, F, and P isotopes have been specifically studied. Magnetic moment value inferences made for these isotopes using Anfis have also been compared with the theoretical results of the Quasiparticle-Phonon Nuclear Method (QPNM) and with the Shell Model calculations. There is a satisfactory agreement between our predictions and the results of these two theories. Besides, the values obtained from the test and train operations are within the minimum error limits (~%0.03-0.04), the reliability of our system has been proven and a study that has not yet been done in the literature has been conducted. Since the Neuro-Fuzzy system will be a first in the field of nuclear technologies, we believe that the outputs of our study will be a good reference for future studies.