Schrodinger Simulation

Simulating the Schrödinger Equation with Python.

This Python module numerically solves the Schrödinger Equation, enabling simulations of quantum systems with arbitrary initial conditions and potentials, including time-dependent ones.

The module supports real-time visualization of wavefunction dynamics and can calculate energy eigenstates and eigenvalues for custom potentials. Animations and plots are automatically handled, but allow for customization if needed.

A Jupyter notebook with examples is included to demonstrate some of its features and capabilities.

Examples

Overview

This project aims to solve the Schrödinger equation numerically. It includes Python scripts to help with setting up and analyzing quantum mechanical problems.

Features

• Implementation of numerical methods for solving the Schrödinger equation.
• Flexibility to define custom initial conditions for the wavefunction.
• Simulate and view wavefunction dynamics in arbitrary potentials, including time-dependent scenarios.
• Find and view energy eigenstates and eigenvalues for arbitrary potentials.
• Jupyter notebook examples for easy understanding.
• Modular code to allow easy extension.

Getting Started

To get started, clone the repository and install the dependencies. The project uses pipenv for managing Python packages.

Prerequisites

• Python 3.11
• Pipenv for dependency management

Installation

1. Clone the repository:

   git clone https://github.com/aydencook03/schrodinger_simulation.git

2. Navigate to the project directory:

   cd schrodinger_simulation

3. Install dependencies with pipenv:

   pipenv install

Running the Examples

A Jupyter notebook is provided to help users learn how to use the Schrödinger equation solver step-by-step and visualize the results interactively.

To run the examples, install the development dependencies, including JupyterLab:

pipenv install --dev

Start a pipenv shell:

pipenv shell

Then open JupyterLab:

jupyter lab Examples.ipynb

Project Structure

• schrodinger.py: Main implementation of the Schrödinger equation solver.
• Examples.ipynb: Jupyter notebook with usage examples.
• Pipfile: Dependency definitions.

Contributing

If you wish to contribute, feel free to fork the repository and submit a pull request. Please ensure your changes include proper documentation and tests.

License

This project is licensed under the MIT License.