senpai VS lammps

Before my radicalisation to anarchism, I started work on SENPAI and released it as MIT software. I wanted to make computational chemistry free and open source to liberate the field.

I'm using my own software! It started out based on the AMBER force fields but it quickly evolved into its own thing. It's called SENPAI, and while I stopped pushing to GitHub like a year or so ago, I didn't remove it from there and its source is available -> https://github.com/Garuda1/senpai

Look into verlet lists or cell lists for your task, which are typically used with a discrete element method such as LAMMPS for what you seem to be describing.

Your choices are an n-body simulation (e.g., LAMMPS) with Coulomb interactions or, if your electrons are sufficiently sparse, a particle-in-cell (e.g., Starfish). Your best bets for visualization are going to be matplotlib or something more user-friendly like Visit or Paraview. Without a neutralizing background, however, your electrons are just going to repel each other, hit the walls, and disappear - there's not going to be much interesting to visualize. What are you actually trying to simulate? With more information maybe you could receive some more targeted advice.

Is this just a personal /learning project? I see "chemical simulations" and think quantum-espresso, LAMMPS, NWChem, etc. If this is a personal project, I apologize for my bluntness above.

Actually, the LAMMPS website has a similar example: Just hover over the "LAMMPS" logo in yellow and blue.

Modify the file to add what you need. In your case, modify the post_force functions in the files, since those will allow you to define the integration steps for the Vicsek model and its variations.