Systematical evaluation of half-lives of proton emission, α decay, cluster radioactivity and spontaneous fission based on Bayesian neural network

Systematical evaluation of half-lives of four decay modes (proton emission, α decay, cluster radioactivity and spontaneous fission) toward a unified description are performed through the Bayesian neural network (BNN) method. In the BNN training, the existing experimental half-lives of nuclei are adopted directly as the target values. As a result, all of the predicated half-lives of the four decay modes agree with the experimental data well, and the BNN approach is possibly useful for evaluations of half-lives of decay modes even if rare/insufficient experimental data are available. In addition, the angular momentum Ι plays an important role in the prediction.