Generative Quantum Machine Learning using Python and Q#

In this tutorial, we'll use a Jupyter notebook to implement Data-driven Quantum Circuit Learning (DDQCL), based on the 2019 paper Training of quantum circuits on a hybrid quantum computer by Zhu et. al.

Prerequisites

• Azure Quantum Workspace
• Python 3.7+
• IQ#
• A few helpful packages:
• numpy
• scipy
• noisyopt
• matplotlib
• jupyterlab

Getting started

Download, install prerequisites, and just run the Jupyter notebook in the src/ directory! Instructions on how to submit jobs to Azure Quantum using Jupyter notebooks are at https://docs.microsoft.com/en-us/azure/quantum/how-to-submit-jobs-with-jupyter-notebooks