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This tutorial contains three labs on Quantum Machine Learning for Generative Modeling - to be completed within a lecture workshop for the Open Data Science Conference 2020. The three labs should be done in order:

  1. Lab 1: Fair and Biased Coin Toss
  2. Lab 2: Entanglement Generator
  3. Lab 3: Quantum Circuit Born Machine (QCBM)

For Lab 3, we have two helper scripts for utility functions (utils.py) and our classical optimizer (pso.py). Please make sure these are in the same folder as the Lab 3 script in order to ensure that you can import functions from these scripts.

Installation

Installation Requirements:

  • Python 3.7 (at least)
  • Python Package NumPy
  • Python Package random2
  • Python Package Matplotlib
  • Jupyter Lab or Notebook
  • PyQuil
  • Quilc
  • Rigetti QVM

Installation Instructions:

If not already installed, please install at least Python Version 3.7. Instructions on installing Python can be found here: https://www.python.org/downloads/. Along with Python 3.7, please install the Python package NumPy. Instructions can be found here: https://numpy.org/install/. Please install the package random2 with instructions found here: https://pypi.org/project/random2/. Please install the package Matplotlib with instructions found here: https://pypi.org/project/matplotlib/.

If not already installed, please install Jupyter Notebook or Jupyter Lab prior to this workshop. Instructions on installing Jupyter can be found here: https://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html.

You can utilize the package manager 'pip' to install Jupyter Lab with 'pip install jupyterlab'.

The last thing you'll need to install is PyQuil. PyQuil is a Python library for quantum programming using Quil, the quantum instruction language developed at Rigetti Computing. Installation instructions can be found here: https://pyquil-docs.rigetti.com/en/stable/start.html.

PyQuil can be installed using 'pip install pyquil'. PyQuil, along with quilc, the QVM, and other libraries, make up what is called the Forest SDK. To make full use of pyQuil, you will need to additionally have installed quilc and the Quantum Virtual Machine (QVM). These can be downloaded together directly from here: https://qcs.rigetti.com/sdk-downloads.

Give it a Try!

Prior to the workshop, try opening your Jupyter Notebook/Lab and make sure everything runs.

First, open up two separate terminal windows for the quilc compiler and the qvm. In the first terminal type 'qvm -S'. In the second terminal type 'quilc -S'

Then input the following code into your Jupyter Notebook:

#load the necessary packages and libraries from pyquil.quil import Program import pyquil.api as api from pyquil.gates import * import matplotlib.pyplot as plt import time import itertools import numpy as np import math qvm = api.QVMConnection()

If no errors pop up when you run it, you're good to go! Looking forward to seeing you at the workshop!