Physics Informed Neural Networks for Solving Dirac Equation in (1+1) Dimension
Year: 2021
Type: dissertation
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
Author: Aigerim Bazarkhanova
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3174842288