2014
DOI: 10.1103/physrevc.90.014303
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Mass predictions of the relativistic mean-field model with the radial basis function approach

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Cited by 49 publications
(31 citation statements)
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“…For very neutron-rich nuclei, the predictions of various mass models can differ by more than a few mega-electron volts. Hybrid models including the use of the radial basis function approach [125,126], the residual proton-neutron interactions [127], and the systematics of the alpha decay energies [128] can provide highly precise predictions for nuclei near the known mass surface; however, the growth of the intrinsic error for nuclei far from the known region remains a serious problem. In this sense, any reliable experimental data can serve as a critical test of existing mass models and guide their further development.…”
Section: Discussionmentioning
confidence: 99%
“…For very neutron-rich nuclei, the predictions of various mass models can differ by more than a few mega-electron volts. Hybrid models including the use of the radial basis function approach [125,126], the residual proton-neutron interactions [127], and the systematics of the alpha decay energies [128] can provide highly precise predictions for nuclei near the known mass surface; however, the growth of the intrinsic error for nuclei far from the known region remains a serious problem. In this sense, any reliable experimental data can serve as a critical test of existing mass models and guide their further development.…”
Section: Discussionmentioning
confidence: 99%
“…The problem accordingly deteriorates the description of nuclear single-neutron separation energies [40]. In this work, we attempt to cure the odd-even deviations found in our previous RBF calculations, which will be presented in Sec.…”
Section: Introductionmentioning
confidence: 99%
“…More details can be found in Ref. [39,40]. In this approach, the solution at point x is represented as a sum of m radial basis functions φ( x − x i ) weighted by an appropriate coefficient ω i , i.e.,…”
Section: Radial Basis Function Approach and Numerical Detailsmentioning
confidence: 99%
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