Missing mass spectroscopy on oxygen isotopes beyond the proton-drip line: mirror symmetry of nuclear shell evolution

The properties of the oxygen isotopes provide diverse examples of progress made in experiments and theory. This chain of isotopes has been studied from beyond the proton drip line in [Formula: see text]O to beyond the neutron drip line in [Formula: see text]O. This short survey starts with the microscopic G matrix approach for [Formula: see text]O of Kuo and Brown in the 1960’s and shows how theory has evolved. The nuclear structure around the doubly-magic nucleus [Formula: see text]O is particularly simple in terms of the nuclear shell model. The nuclear structure around the doubly-magic nucleus [Formula: see text]O exhibits the coexistence of single-particle and collective structure.

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NUCLEI BEYOND THE PROTON DRIP-LINE

Annual Review of Nuclear and Particle Science ◽

10.1146/annurev.nucl.47.1.541 ◽

1997 ◽

Vol 47 (1) ◽

pp. 541-590 ◽

Cited By ~ 192

Author(s):

P. J. Woods ◽

C. N. Davids

Keyword(s):

Drip Line ◽

Proton Drip Line

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The structure and shape of exotic nuclei beyond the proton drip-line

10.1063/1.3039827 ◽

2008 ◽

Author(s):

L. S. Ferreira ◽

E. Maglione ◽

P. Arumugam ◽

Ismail Boztosun ◽

A. B. Balantekin

Keyword(s):

Drip Line ◽

Exotic Nuclei ◽

Proton Drip Line

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Mapping the proton drip line from to

Nuclear Physics A ◽

10.1016/s0375-9474(00)00375-4 ◽

2001 ◽

Vol 679 (3-4) ◽

pp. 481-493 ◽

Cited By ~ 25

Author(s):

G.A. Lalazissis ◽

D. Vretenar ◽

P. Ring

Keyword(s):

Drip Line ◽

Proton Drip Line

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Proton drip line evaluation by complementing the Finite Range Droplet Model with neural networks

HNPS Proceedings ◽

10.12681/hnps.2608 ◽

2020 ◽

Vol 15 ◽

pp. 258

Author(s):

S. Athanasopoulos ◽

E. Mavrommatis ◽

K. A. Gernoth ◽

J. W. Clark

Keyword(s):

Neural Network ◽

Neural Networks ◽

Atomic Mass ◽

Drip Line ◽

Finite Range ◽

Mass Excess ◽

Droplet Model ◽

Mass Model ◽

Proton Drip Line ◽

The One

We evaluate the location of the proton drip line in the regions 31≤Z≤49 and 73≤Z≤91 based on the one- and two-proton separation energies predicted by our latest Hybrid Mass Model. The latter is constructed by complementing the mass-excess values ΔM predicted by the Finite Range Droplet Model (FRDM) of Moeller et al. with a neural network model trained to predict the differences ΔMexp − ΔMFRDM between these values and the experimental mass-excess values published in the 2003 Atomic Mass Evaluation AME03.

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