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

Summary

In this chapter, we covered various simulators. You now have the skills to leverage various simulators to simulate running circuits on a quantum computer and obtain specific content from the circuits, such as state vectors, a unitary matrix, and any scheduled pulses.

We also covered various visualization techniques. The skills that you have gained will help you visualize the various pieces of information from the simulator, such as visualizing the state and phase information of a qubit using the QSphere and plotting state vector graphs. And finally, we looked into the noise models that Aer provides by either extracting the noise from an existing quantum computer, or creating our own noise models and applying them to the simulators.

In the next chapter, we will learn how to characterize and mitigate noise using Ignis. This will allow us to optimize the performance of the quantum computer and increase its computational power. We will also learn how to measure a quantum...