Reaching for the limit of stability

Abstract: In this project, calculations for the total binding energy of all even-even nuclei available from experimental data are performed using the HFBTHO program. An artificial neural network is applied to train the information obtained from the HFBTHO calculations and predict the binding energy for the nuclei. The results show impressive improvements to the HFBTHO program. In recent years, the combination of scientific research and machine learning algorithms has become a popular and successful practice. Although it is hard to judge whether an algorithm is good enough, especially with the rapid development of computer science, the application of machine learning in nuclear models can be reliable and promising in predicting the nuclear properties.