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Dancing with Qubits - Second Edition

You're reading from  Dancing with Qubits - Second Edition

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636754
Pages 684 pages
Edition 2nd Edition
Languages
Author (1):
Robert S. Sutor Robert S. Sutor
Profile icon Robert S. Sutor

Table of Contents (26) Chapters

Preface I Foundations
Why Quantum Computing They’re Not Old, They’re Classics More Numbers Than You Can Imagine Planes and Circles and Spheres, Oh My Dimensions 6 What Do You Mean “Probably”? II Quantum Computing
One Qubit Two Qubits, Three Wiring Up the Circuits From Circuits to Algorithms Getting Physical III Advanced Topics
Considering NISQ Algorithms Introduction to Quantum Machine Learning Questions about the Future Afterword
A Quick Reference B Notices C Production Notes Other Books You May Enjoy
References
Index
Appendices

For whom did I write this book?

This book is for anyone who has a very healthy interest in mathematics and wants to start learning about the computer science, engineering, and a bit of the physics of quantum computing. I review the basic math, but things move quickly, so we can dive deeply into an exposition of how to work with qubits and quantum algorithms. There are exercises in every chapter for you to test and deepen your knowledge.

While this book contains a lot of math, it is not of the definition-theorem-proof variety. I’m more interested in presenting the topics to give you insight into the relationships between the ideas than giving you a strictly formal development of all results.

Another goal is to prepare you to read more advanced texts and articles on the subject, perhaps returning here to understand some core topic. You do not need to be a mathematician, and certainly not a physicist, to read this book, nor do you need to understand quantum mechanics beforehand.

At several places in the book, I give some code examples using Python 3. Consider these extra and not required, but if you know Python, they may help your understanding. programming language$Python

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