Book Image

Learn Quantum Computing with Python and IBM Quantum Experience

By : Robert Loredo
Book Image

Learn Quantum Computing with Python and IBM Quantum Experience

By: Robert Loredo

Overview of this book

IBM Quantum Experience is a platform that enables developers to learn the basics of quantum computing by allowing them to run experiments on a quantum computing simulator and a real quantum computer. This book will explain the basic principles of quantum mechanics, the principles involved in quantum computing, and the implementation of quantum algorithms and experiments on IBM's quantum processors. You will start working with simple programs that illustrate quantum computing principles and slowly work your way up to more complex programs and algorithms that leverage quantum computing. As you build on your knowledge, you’ll understand the functionality of IBM Quantum Experience and the various resources it offers. Furthermore, you’ll not only learn the differences between the various quantum computers but also the various simulators available. Later, you’ll explore the basics of quantum computing, quantum volume, and a few basic algorithms, all while optimally using the resources available on IBM Quantum Experience. By the end of this book, you'll learn how to build quantum programs on your own and have gained practical quantum computing skills that you can apply to your business.
Table of Contents (21 chapters)
1
Section 1: Tour of the IBM Quantum Experience (QX)
5
Section 2: Basics of Quantum Computing
9
Section 3: Algorithms, Noise, and Other Strange Things in Quantum World
18
Assessments
Appendix A: Resources

Monitoring and tracking jobs

The Qiskit Notebooks hosted on IQX are built on Jupyter Notebooks. This allows us to use some of the features that are available to us to enhance our experience and optimize our time when programming quantum circuits. One of these features is the ability to track jobs in real time while they are executing. We'll try this out here with a test circuit using the following steps:

  1. First, we'll create a new Qiskit notebook and enter the following in a new cell:
    # Import the Qiskit Jupyter tools 
    from qiskit.tools import jupyter
  2. Now that we have imported the Qiskit Jupyter tools and have created our provider, we can launch the job tracking widget:
    # Initialize the job tracker to automatically track all # jobs
    %qiskit_job_watcher

    The preceding code will launch the Job Watcher widget to the top left of your Qiskit notebook to track your jobs.

  3. We'll then create and execute a circuit to test the job watcher:
    # Let's run a simple circuit...