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

There are many algorithms that implement many of the techniques we covered in this chapter, such as amplitude amplification, oracles, phase kickbacks, and much more, which you will see used in many other algorithms, such as the quantum amplitude estimation and variational quantum Eigensolver algorithms.

I do strongly suggest trying variations of these algorithms yourself to get a better feel and understanding as to how they work.

We also used the algorithms that are built into Qiskit Aqua, which allows you as a researcher to leverage the algorithms. You have now gained the skills to integrate these algorithms into your existing research or applications without having to worry about developing circuits, mitigating against noise, or any of the other components that make up an algorithm in Aqua. This book has already done the heavy lifting for you, so you just have to implement the algorithm and process the results as you see fit.