This project aims to solve the time-independent molecular Schrödinger equation by employing physics-informed machine learning techniques. A cornerstone of molecular physics, understanding electron distributions within molecules is essential for ascertaining their chemical properties.
The main objective is to find eigenvalues and eigenstates of the time-independent Schrödinger operator for the Hydrogen atom. Currently, the project generates exact solutions for the Hydrogen atom as a baseline and attempts to approximate these solutions using Physics-Informed Neural Networks (PINNs).
- Clone the repository to your local machine: ```bash git clone https://github.com/your_username/molecular-schrodinger-solver.git ```
- Navigate to the project directory: ```bash cd molecular-schrodinger-solver ```
- Install dependencies (assuming you have Python and pip installed): ```bash pip install tensorflow numpy scipy ```
To generate exact solutions for the Hydrogen atom, run:
```bash python hydrogen.py ```
To solve the Schrödinger equation for the Hydrogen atom using PINNs, run:
```bash python hydrogen-pinn.py ```
The project currently provides exact solutions for the Hydrogen atom, serving as a benchmark. Comparison of these exact solutions with those obtained from the PINN model will be conducted as the project evolves.
This project is licensed under the MIT License - see LICENSE.md for details.