2023-SQAI-Demo: Quantum Deep Learning

Introduction

This is an introductory technical demonstration on how to develop and train a quantum neural network with various quantum circuit configurations. The demonstration is built on top of Qiskit and Qiskit machine learning framework from IBM Quantum. The code was originally developed for the IBM Qiskit tutorial on the latest quantum machine learning framework. The original tutorial can be found here

Editor and Conference Speaker

Mark Chen

Getting Started

Set-up the development environment:

pip install -r requirements.txt

Recommanded Python environment:

• Python 3.8
• Python 3.10

Run the demo:

Basic introduction to quantum neural network

python src/quantum_neural_network.py

Quantum neural network with variational quantum circuit for classification and regression

python src/quantum_classifier_regressor.py