## 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.