Diffuseness effect and radial basis function network for optimizing α decay calculations

A radial basis function network (RBFN) approach is adopted for the first time to optimize the calculation of decay half-life in the generalized liquid drop model (GLDM), while concurrently incorporating the surface diffuseness effect. The calculations presented herein agree closely with the experime...

Full description

Saved in:
Bibliographic Details
Published in:Chinese physics C 2021-02, Vol.45 (2), p.24105
Main Authors: Ma, Na-Na, Bao, Xiao-Jun, Zhang, Hong-Fei
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A radial basis function network (RBFN) approach is adopted for the first time to optimize the calculation of decay half-life in the generalized liquid drop model (GLDM), while concurrently incorporating the surface diffuseness effect. The calculations presented herein agree closely with the experimental half-lives for 68 superheavy nuclei (SHN), achieving a remarkable reduction of 40% in the root-mean-square (rms) deviations of half-lives. Furthermore, using the RBFN method, the half-lives for four SHN isotopes, 252-288 Rf, 272-310 Fl, 286-316 119, and 292-318 120, are predicted using the improved GLDM with the diffuseness correction and the decay energies from WS4 and FRDM as inputs. Therefore, we conclude that the diffuseness effect should be embodied in the proximity energy. Moreover, increased application of neural network methods in nuclear reaction studies is encouraged.
ISSN:1674-1137
2058-6132
DOI:10.1088/1674-1137/abcc5c