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A Practical Guide to Quantum Machine Learning and Quantum Optimization

You're reading from   A Practical Guide to Quantum Machine Learning and Quantum Optimization Hands-on Approach to Modern Quantum Algorithms

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Product type Paperback
Published in Mar 2023
Publisher Packt
ISBN-13 9781804613832
Length 680 pages
Edition 1st Edition
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Authors (2):
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Elías F. Combarro Fernández-Combarro Álvarez Elías F. Combarro Fernández-Combarro Álvarez
Author Profile Icon Elías F. Combarro Fernández-Combarro Álvarez
Elías F. Combarro Fernández-Combarro Álvarez
Samuel González Castillo Samuel González Castillo
Author Profile Icon Samuel González Castillo
Samuel González Castillo
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Table of Contents (27) Chapters Close

Preface 1. Part I: I, for One, Welcome our New Quantum Overlords
2. Chapter 1: Foundations of Quantum Computing FREE CHAPTER 3. Chapter 2: The Tools of the Trade in Quantum Computing 4. Part II: When Time is Gold: Tools for Quantum Optimization
5. Chapter 3: Working with Quadratic Unconstrained Binary Optimization Problems 6. Chapter 4: Adiabatic Quantum Computing and Quantum Annealing 7. Chapter 5: QAOA: Quantum Approximate Optimization Algorithm 8. Chapter 6: GAS: Grover Adaptive Search 9. Chapter 7: VQE: Variational Quantum Eigensolver 10. Part III: A Match Made in Heaven: Quantum Machine Learning
11. Chapter 8: What Is Quantum Machine Learning? 12. Chapter 9: Quantum Support Vector Machines 13. Chapter 10: Quantum Neural Networks 14. Chapter 11: The Best of Both Worlds: Hybrid Architectures 15. Chapter 12: Quantum Generative Adversarial Networks 16. Part IV: Afterword and Appendices
17. Chapter 13: Afterword: The Future of Quantum Computing
18. Assessments 19. Bibliography
20. Index
21. Other Books You May Enjoy Appendix A: Complex Numbers
1. Appendix B: Basic Linear Algebra 2. Appendix C: Computational Complexity 3. Appendix D: Installing the Tools 4. Appendix E: Production Notes

Chapter 1
Foundations of Quantum Computing

The beginning is always today.
— Mary Shelley

You may have heard that the mathematics needed to understand quantum computing is arcane, mysterious and difficult…but we utterly disagree! In fact, in this chapter, we will introduce all the concepts that you will need in order to follow the quantum algorithms that we will be studying in the rest of the book. Actually, you may be surprised to see that we will only rely on some linear algebra and a bit of (extremely simple) trigonometry.

We shall start by giving a quick overview of what quantum computing is, what the current state of the art is, and what the main applications are expected to be. After that, we will introduce the model of quantum circuits. There are several computational models for quantum computing, but this is the most popular one and, moreover, it's the one that we will be using throughout most of the book. Then, we will describe in detail what qubits are, how we can operate on them by using quantum gates, and how we can retrieve results by performing measurements. We will start with the simplest possible case — just a humble qubit! Then, we will steadily build upon that until we learn how to work with as many qubits as we want.

This chapter will cover the following topics:

  • Quantum computing: the big picture

  • The basics of the quantum circuit model

  • Working with one qubit and the Bloch sphere

  • Working with two qubits and entanglement

  • Working with multiple qubits and universality

After reading this chapter, you will have acquired a solid understanding of the fundamentals of quantum computing and you will be more than ready to learn how practical quantum algorithms are developed.

You have been reading a chapter from
A Practical Guide to Quantum Machine Learning and Quantum Optimization
Published in: Mar 2023
Publisher: Packt
ISBN-13: 9781804613832
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