Neural networks represent densities in a variational extended Thomas-Fermi model, yielding binding energies within 0.5% of prior ETF results and reproducing nuclear pasta phases.
author Mart\' nez-Pinedo, G
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Three-dimensional band-structure calculations in the BCS approximation within HFB theory find that only 8% of free neutrons participate in superflow at baryon density 0.03 fm^{-3}, independent of the pairing gap.
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Neural-Network-Based Variational Method in Nuclear Density Functional Theory: Application to the Extended Thomas-Fermi Model
Neural networks represent densities in a variational extended Thomas-Fermi model, yielding binding energies within 0.5% of prior ETF results and reproducing nuclear pasta phases.
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Superfluid fraction in the crystalline crust of a neutron star: role of BCS pairing
Three-dimensional band-structure calculations in the BCS approximation within HFB theory find that only 8% of free neutrons participate in superflow at baryon density 0.03 fm^{-3}, independent of the pairing gap.