Axect/Neural_Hamilton
Official implementation of the paper "Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?"
This project helps physicists and researchers model complex physical systems by predicting how they evolve over time. Instead of solving intricate differential equations, it takes descriptions of physical forces (potential functions) and generates accurate trajectories and system behaviors. The ideal users are computational physicists, theoretical physicists, and engineers working with dynamic systems.
Use this if you need to simulate Hamiltonian systems and want to leverage AI to predict their evolution more efficiently and accurately than traditional numerical methods, especially for complex or long-duration scenarios.
Not ideal if your primary goal is to derive analytical solutions to Hamiltonian equations or if you are not working with dynamic physical systems.
Stars
14
Forks
—
Language
Python
License
MIT
Category
Last pushed
Feb 09, 2026
Commits (30d)
0
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