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J. W. Clark

5 papers hereh-index 5151 citations9 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • last author3

Across the 3 of 5 papers where every author was matched, so the position is known.

fields
  • nucl-th5
same name
  • J. W. Clark — 41 papers, h 14
  • J. W. Clark — 33 papers, h 32
  • J. W. Clark — 10 papers, h 7
  • J. W. Clark — 2 papers
  • J. W. Clark — 1 paper, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20032017
most citedNuclear mass systematics using neural networks

98 citations · 144 across the 4 of their papers we have counts for

collaborators

4 papers

nucl-th2017★ 15 cited

Three-nucleon forces and superfluidity in neutron matter

P. Papakonstantinou, J. W. Clark

The existence of superfluidity of the neutron component in the core of a neutron star, associated specifically with triplet P−wave pairing, is currently an open question that is…

nucl-th2016★ 16 cited

Microscopic Study of 1S0​ Superfluidity in Dilute Neutron Matter

G. E. Pavlou, E. Mavrommatis, Ch. Moustakidis +1

Singlet S-wave superfluidity of dilute neutron matter is studied within the correlated BCS method, which takes into account both pairing and short-range correlations. First, the…

nucl-th2005

One and two proton separation energies from nuclear mass systematics using neural networks

S. Athanassopoulos, E. Mavrommatis, K. A. Gernoth +1

We deal with the systematics of one and two proton separation energies as predicted by our latest global model for the masses of nuclides developed with the use of neural networks.…

nucl-th2003★ 98 cited

Nuclear mass systematics using neural networks

S. Athanassopoulos, E. Mavrommatis, K. A. Gernoth +1

New global statistical models of nuclidic (atomic) masses based on multilayered feedforward networks are developed. One goal of such studies is to determine how well the existing d…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.