Flows: classical, Hamiltonian, from OCP and more
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Updated
Sep 8, 2024 - Julia
Flows: classical, Hamiltonian, from OCP and more
Python library for quantum systems and simulation
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
Dash App - simulation of double pendulum equations of motion
Solutions to Mathematical Methods of Classical Mechanics by V.A.Arnold
pyHamSys is a Python package for scientific computations involving Hamiltonian systems
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
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
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