My Github is here.
It features my favourite tools for solving numerical problems in physics. Built over the last few years, they use basic techniques like adaptive Runge-Kutta, adaptive numerical integration, and Monte Carlo.
Example: 2D Ising Model
For example, for my statistcal mechanics course, I built a Jupyter Notebook to analyze the 2D Ising Model (lattice of spins where each spin's direction is influenced by the 8 spins closest to it). Here are some of the results.
Example: Brownian Motion
In this exercise, I investigate discrete Brownian path of a penguin with randomized velocity at each time step (sometimes physics professors have a little fun with assignment problems). In the Notebook, I generate the bath and investigate that the average correlation between velocities at different times is proportional to the exponential of the time difference.