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By means of Monte Carlo methods, we perform a full error analysis on the Duflo-Zucker mass model. In particular, we study the presence of correlations in the residuals to obtain a more realistic estimate of the error bars on the predicted binding energies. To further reduce the discrepancies between model prediction and experimental data we also apply a Multilayer Perceptron Neural Network. We show that the root mean square of the model further reduces of roughly 40%. We then use the resulting models to predict the composition of the outer crust of a non accreting neutron star. We provide a first estimate of the impact of error propagation on the resulting equation of state of the system.
We investigated the structure of the low density regions of the inner crust of neutron stars using the Hartree-Fock-Bogoliubov (HFB) model to predict the proton content $Z$ of the nuclear clusters and, together with the lattice spacing, the proton co
A number of observed phenomena associated with individual neutron star systems or neutron star populations find explanations in models in which the neutron star crust plays an important role. We review recent work examining the sensitivity to the slo
We investigate the dynamics of a quantized vortex and a nuclear impurity immersed in a neutron superfluid within a fully microscopic time-dependent three-dimensional approach. The magnitude and even the sign of the force between the quantized vortex
We demonstrate that the high-quality cooling data observed for the young neutron star in the supernova remnant Cassiopeia A over the past 10 years--as well as all other reliably known temperature data of neutron stars--can be comfortably explained wi
We present an error band on neutron matter properties at finite temperature (finite-T) which comprehends uncertainties on the nuclear interaction, the many-body method convergence, and the thermodynamical consistency of the approach. This study provi