Abstract:
The Dirac equation plays a fundamental role in quantum physics and its
exact solutions are of utmost importance. In this study we solved Linear and Nonlin ear Dirac equation in (1+1) dimension and obtained analytical solutions. Moreover we
have implemented Physics Informed Neural Networks to get approximate solutions of
Linear and Nonlinear Dirac equation in (1+1) dimension. During the experiments we
observed that Physics Informed Neural Networks are not capable of providing good solutions for any given time and faced the problem of choosing appropriate weights for
each loss function. Therefore, architecture of multilayer feedforward neural networks for
approximating solutions of Dirac equation needs further investigation