Narrow Results

The ground state and first intrinsic excited state of superheavy nuclei with Z = 120 and N = 160–204 are investigated using both nonrelativistic Skyrme–Hartree–Fock (SHF) and the axially deformed relativistic mean field (RMF) formalisms. We employ a simple BCS pairing approach for calculating the energy contribution from pairing interaction. The results for isotopic chain of binding energy (BE), quadrupole deformation parameter, two neutron separation energies and some other observables are compared with the finite range droplet model (FRDM) and some recent macroscopic–microscopic calculations. We predict superdeformed ground state solutions for almost all the isotopes. Considering the possibility of magic neutron number, two different modes of α-decay chains ²⁹²120 and ³⁰⁴120 are also studied within these frameworks. The Q_α-values and the half-life for these two different modes of decay chains are compared with FRDM and recent macroscopic–microscopic calculations. The calculation is extended for the α-decay chains of ²⁹²120 and ³⁰⁴120 from their excited state configuration to respective configuration, which predicts long half-life (in seconds).

For the Riemannian space, built from the collective coordinates used within nuclear models, an additional interaction with the metric is investigated, using the collective equivalent to Einstein's curvature scalar. The coupling strength is determined using a fit with the AME2003 ground state masses. An extended finite-range droplet model including curvature is introduced, which generates significant improvements for light nuclei and nuclei in the trans-fermium region.

The phenomenological formula for ground state binding energy derived earlier [G. Gangopadhyay, Int. J. Mod. Phys. E20 (2011) 179] has been modified. The parameters have been obtained by fitting the latest available tabulation of experimental values. The major modifications include a new term for pairing and introduction of a new neutron magic number at N = 160. The new formula reduced the root mean square deviation to 363keV, a substantial improvement over the previous version of the formula.

In recent years, artificial neural networks and their applications for large data sets have become a crucial part of scientific research. In this work, we implement the Multilayer Perceptron (MLP), which is a class of feedforward artificial neural network (ANN), to predict ground-state binding energies of atomic nuclei. Two different MLP architectures with three and four hidden layers are used to study their effects on the predictions. To train the MLP architectures, two different inputs are used along with the latest atomic mass table and changes in binding energy predictions are also analyzed in terms of the changes in the input channel. It is seen that using appropriate MLP architectures and putting more physical information in the input channels, MLP can make fast and reliable predictions for binding energies of atomic nuclei, which is also comparable to the microscopic energy density functionals.