Predictions of nuclear charge radii with the radial basis function approach and linear relationship

【摘要】 The linear relationship between the charge radius deviations for nuclei(Z,N) and those for(Z,N-2) is observed in the predictions of the WS*radius formula and HFB25 model.Together with the linear relationship,a modified radial basis function(RBFlr) approach is proposed to further improve the accuracy of the models in charge radius predictions.The root-mean-square deviation with respect to 995 measured nuclear charge radii falls to 0.007 fm,and the charge radii of Ca isotopes can be much better reproduced.In addition,based on the proposed approach,the charge radii of 331 unmeasured nuclei are predicted.This linear correlation combined with RBFlr has the potential to become a typical practice of physically guided machine learning approaches in nuclear physics.更多还原

【Abstract】 The linear relationship between the charge radius deviations for nuclei(Z,N) and those for(Z,N-2) is observed in the predictions of the WS*radius formula and HFB25 model.Together with the linear relationship,a modified radial basis function(RBFlr) approach is proposed to further improve the accuracy of the models in charge radius predictions.The root-mean-square deviation with respect to 995 measured nuclear charge radii falls to 0.007 fm,and the charge radii of Ca isotopes can be much better reproduced.In addition,based on the proposed approach,the charge radii of 331 unmeasured nuclei are predicted.This linear correlation combined with RBFlr has the potential to become a typical practice of physically guided machine learning approaches in nuclear physics.更多还原