redx94 / QGAN_Project

An advanced AI application integrating quantum computing capabilities with deep learning frameworks to create powerful hybrid classical-quantum AI models. This technology aims to unlock new applications in fields such as chemistry, materials science, drug discovery, finance, and cryptography.

Quantum Generative Adversarial Network (QGAN)

Project Description

An advanced AI application integrating quantum computing capabilities with deep learning frameworks to create powerful hybrid classical-quantum AI models. This technology aims to unlock new applications in fields such as chemistry, materials science, drug discovery, finance, and cryptography.

Features

• Quantum and Classical Hybrid Model
• Leveraging Pennylane for Quantum Circuit Simulations
• Advanced GAN Architecture

Installation

Clone the repository:

git clone https://github.com/redx94/QGAN_Project.git

Navigate to the project directory:

cd QGAN_Project

Install the required packages:

pip install -r requirements.txt

Usage

Train the QGAN model:

python qgan/train.py

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

This project is licensed under the terms of the Commercial Use License and the Public Non-Commercial License. See the LICENSE file for details.

Call for Professionals

We are seeking professionals in the fields of quantum computing, AI, and deep learning to collaborate on this project. If you are interested, please contact us at [e-mail].