Official implementation of the paper "Neural Hamilton: Can A.I. Understand Hamiltonian Mechanics?"

pyHamSys is a Python package for scientific computations involving Hamiltonian systems

Symplectic integration of Hamiltonian systems. Zymplectic is a pre-compiled GUI and engine with 2D/3D-graphics bundled with more than 80 example dynamical systems in cpp format

Flows: classical, Hamiltonian, from OCP and more

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

Python library for quantum systems and simulation

Dash App - Simulation of double pendulum equations of motion

Solutions to Mathematical Methods of Classical Mechanics by V.A.Arnold

The package phlearn for modelling pseudo-Hamiltonian systems by pseudo-Hamiltonian neural networks (PHNN), for ODEs and PDEs

Plotted phase space trajectories for different mechanical systems using Python.

Numerical results for deterministic dynamics of a system coupled to a finite and chaotic bath.

Theoretical project regarding hamiltonian and lagrangian neural network

Renormalization for the break-up of invariant tori in Hamiltonian flows

Symplectic Recurrent Neural Networks

One-dimensional Vlasov-Poisson equation and its Hamiltonian fluid reductions

Numerical work related to Clock Space Hamiltonian Simulation

Conjugation method in configuration space for invariant tori of Hamiltonian systems

Code for the paper "Sparse Symplectically Integrated Neural Networks"

Port-Hamiltonian Approach to Neural Network Training

Sampling-based approach to analyse neural networks using TensorFlow