A collection of Python-based numerical simulations and computational physics projects demonstrating applied methods in simulations, numerical integration, and visualization.
1. Simulation of Planetary Motion Using Euler Method
Simulates a planet orbiting a star under Newtonian gravity using the Euler method. Visualizes the orbital path and demonstrates numerical error accumulation over time.
2. Analysis of How an Object Orients in 3D Space
Simulates the rotation of a rigid 3D object (cube) using rotation matrices, Euler angles, and quaternions. Includes plots of angles/quaternions and an animated 3D rotation.
3. Calculating Ground State Energy of Harmonic Oscillator (Variational Quantum Monte Carlo)
Uses a variational Monte Carlo method to estimate the ground state energy of a 1D harmonic oscillator. Computes local energy for a trial wavefunction and finds the optimal variational parameter.
4. Damped Driven Pendulum Simulation
Simulates the dynamics of a damped and driven pendulum using numerical integration (Euler/Runge-Kutta). Visualizes periodic, quasi-periodic, and chaotic motion.
- Open the corresponding Jupyter notebooks in Google Colab or Jupyter Notebook.
- Run all cells to reproduce simulations, plots, and animations.
- Python 3.x
- numpy
- matplotlib
- scipy (for some projects)