ẋ = {x, H}
Symbolic Dynamics
Derive equations of motion directly from assumptions, Hamiltonians, brackets, and coordinate choices.
Symbolic Mechanics / Computational Geometry
Symbolic computation for deriving, simplifying, and visualizing Hamiltonian, metriplectic, and Lie-Poisson dynamical systems.

Overview
This project connects computer algebra with Hamiltonian mechanics to make complex dynamical systems easier to derive, inspect, and visualize. The workflow uses symbolic manipulation to compute Poisson brackets, detect Casimirs, simplify vector fields, characterize equilibria, and prepare structured visualizations of the resulting phase geometry.
ẋ = {x, H}
Derive equations of motion directly from assumptions, Hamiltonians, brackets, and coordinate choices.
{C, f} = 0
Expose conserved quantities, degeneracies, symmetries, and dissipative extensions before plotting.
∇H · XH = 0
Turn symbolic reductions into phase portraits, equilibrium diagrams, and geometric level sets.
Systems Studied






Method Pipeline
coordinates, parameters
H(q, p)
{f, g}
X_H
C_i
∇H = 0
flow + leaves
Visual Results





Key Mathematical Ideas
XH = J∇H
A Hamiltonian packages energy and constraints into a scalar generator whose derivatives define motion.
Code / Reproducibility
The computation scripts derive dynamics, characterize equilibria, identify structure-preserving quantities, and generate visualization-ready phase data.
spring_dynamics.mw
pendulum_dynamics.mw
rotating_body_dynamics.mw
derive_hamiltonian()
compute_poisson_bracket()
solve_equilibria()
render_phase_portrait()Citation
@article{bajaj2026computer_algebra_hamiltonian,
title = {Computer Algebra Meets Hamiltonian Geometry},
author = {Bajaj, Chandrajit},
journal = {Maple Transactions},
year = {2026}
}