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phyics

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This project implements a Physics-Informed Neural Network (PINN) using DeepXDE to approximate the gravitational potential field of a two-body system (e.g., Earth and Moon). By embedding Newtonian physics laws into the loss function, the model learns to satisfy both data-driven and physical constraints, demonstrating the fusion of AI and physics.

  • Updated Nov 9, 2025
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