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Essential Mathematics for Quantum Computing

You're reading from   Essential Mathematics for Quantum Computing A beginner's guide to just the math you need without needless complexities

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801073141
Length 252 pages
Edition 1st Edition
Languages
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Author (1):
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Leonard S. Woody III Leonard S. Woody III
Author Profile Icon Leonard S. Woody III
Leonard S. Woody III
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Table of Contents (20) Chapters Close

Preface 1. Section 1: Introduction
2. Chapter 1: Superposition with Euclid FREE CHAPTER 3. Chapter 2: The Matrix 4. Section 2: Elementary Linear Algebra
5. Chapter 3: Foundations 6. Chapter 4: Vector Spaces 7. Chapter 5: Using Matrices to Transform Space 8. Section 3: Adding Complexity
9. Chapter 6: Complex Numbers 10. Chapter 7: EigenStuff 11. Chapter 8: Our Space in the Universe 12. Chapter 9: Advanced Concepts 13. Section 4: Appendices
14. Other Books You May Enjoy Appendix 1: Bra–ket Notation 1. Appendix 2: Sigma Notation 2. Appendix 3: Trigonometry 3. Appendix 4: Probability 4. Appendix 5: References

Definitions

Let's start by getting some basic definitions out of the way. The word experiment is used in probability theory to denote the execution of a procedure that produces a random outcome. Examples of experiments are flipping a coin or rolling dice. In quantum computing, an experiment is measuring a qubit.

A sample space is the set of all possible outcomes of an experiment. It is usually denoted by Ω (the upper case Greek letter omega). The set Ω for a fair coin is {Heads, Tails}. The set Ω for one die is {1, 2, 3, 4, 5, 6}. The set Ω for a qubit when measured in the Z basis is {|0⟩, |1⟩}.

An event (E) is a subset of Ω. Every outcome is a subset of size 1 – for example, {Heads} and {Tails} are events for a fair coin. But as we saw in Chapter 3, Foundations, subsets also include the empty set ∅ and the whole set itself, which is Ω in this case. The set of all events is called an event space and is usually...

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