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

Building a coin-flipping experiment

If you've ever taken a course in probability and statistics, you might have seen the coin flip example. In this example, you are given an unbiased coin to flip multiple times and track the results of each flip (experiment) as either heads or tails. What this experiment illustrates is that with an unbiased coin and enough samples, you will see that the probability of either heads or tails start to converge to about 50%.

This means that, after running a sufficient number of experiments, the number of times the coin lands on heads becomes very closely equal to the number of times that it lands on tails.

Let's take a moment to make an important note regarding the previously stated analogy with respect to the reality of the preceding experiment. It has been proven that in many ways, any coin could be easily made biased so that when it is flipped, it can land on the same side each time.

That being said, I want to ensure that this is...