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 Chamel, N
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Derives exact expressions for pressure and chemical potentials in the neutron star inner crust within Hartree-Fock and extended Thomas-Fermi frameworks, applicable to catalyzed and accreted matter, with examples using BSk24.
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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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Pressure and chemical potentials in the inner crust of a cold neutron star within Hartree-Fock and extended Thomas-Fermi methods
Derives exact expressions for pressure and chemical potentials in the neutron star inner crust within Hartree-Fock and extended Thomas-Fermi frameworks, applicable to catalyzed and accreted matter, with examples using BSk24.