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In this study, we introduce a novel approach for deriving the solution of the ideal force-free steady-state pulsar magnetosphere in three dimensions. Our method involves partitioning the magnetosphere into the regions of closed and open field lines, and subsequently training two custom Physics Informed Neural Networks to generate the solution within each region. We periodically modify the shape of the boundary separating the two regions (the separatrix) to ensure pressure balance throughout. Our approach provides an effective way to handle mathematical contact discontinuities in force-free electrodynamics. We present preliminary results in axisymmetry, which underscore the significant potential of our method. Finally, we discuss the challenges and limitations encountered while working with Neural Networks, thus providing valuable insights from our experience. [ABSTRACT FROM AUTHOR]

This paper deals with heavy-ion peripheral reactions in the Fermi energy region for the production of neutron-rich isotopes. Experimental data of projectile fragments from the reactions of an 40Ar beam at 15 MeV/nucleon with 64Ni and 58Ni targets, collected with the MARS spectrometer at the Cyclotron Institute of Texas A&M University, are considered. Momentum distributions, which provide valuable information on the reaction mechanisms, are extracted and compared with two types of calculations: These are, the Deep Inelastic Transfer (DIT) model and the microscopic Constrained Molecular Dynamics model (CoMD). For the latter, the parameters of the original code were systematically varied in order to achieve an overall satisfactory description of the experimental data. Our results will be discussed.