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Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum

By : Robert Loredo
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Learn Quantum Computing with Python and IBM Quantum

Learn Quantum Computing with Python and IBM Quantum

By: Robert Loredo

Overview of this book

IBM Quantum Lab 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 on several real quantum computers. Updated with new examples and changes to the platform, this edition begins with an introduction to the IBM Quantum dashboard and Quantum Information Science Kit (Qiskit) SDK. You will become well versed with the IBM Quantum Composer interface as well as the IBM Quantum Lab. You will learn the differences between the various available quantum computers and simulators. Along the way, you’ll learn some of the fundamental principles regarding quantum mechanics, quantum circuits, qubits, and the gates that are used to perform operations on qubits. As you build on your knowledge, you’ll understand the functionality of IBM Quantum and the developer-focused resources it offers to address key concerns like noise and decoherence within a quantum system. You’ll learn how to monitor and optimize your quantum circuits. Lastly, you’ll look at the fundamental quantum algorithms and understand how they can be applied effectively. By the end of this quantum computing book, you'll know how to build quantum programs and will have gained a practical understanding of quantum computation that you can apply to your business.
Table of Contents (18 chapters)
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14
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15
Index

Technical requirements

In this chapter, it is expected that you are familiar with the basics of quantum circuits described in previous chapters, such as creating and executing quantum circuits, obtaining backend properties and configurations, and customizing and visualizing circuit diagrams, and you should have knowledge of qubit logic gate operators and states. Also, some familiarity with noise effects such as decoherence time would be ideal; however, we will cover some of the basics in this chapter as a refresher. You will need to install the latest version of qiskit-aer to run the notebooks in this chapter; details can be found in the Qiskit documentation: https://qiskit.github.io/qiskit-aer/getting_started.html.

Here is the full source code used throughout this book: https://github.com/PacktPublishing/Learning-Quantum-Computing-with-Python-and-IBM-Quantum-Second-Edition.

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