Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801073141
Length 252 pages
Edition 1st Edition
Languages
Arrow right icon
Author (1):
Arrow left icon
Leonard S. Woody III Leonard S. Woody III
Author Profile Icon Leonard S. Woody III
Leonard S. Woody III
Arrow right icon
View More author details
Toc

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

Tensor products

Tensor products are a way to combine vector spaces. One of the postulates of quantum mechanics is that the state of a qubit is completely described by a unit vector in a Hilbert space. The problem then becomes how to deal with more than one qubit. This is where a tensor product comes in. Each qubit has its own Hilbert space, and to describe many qubits as a system, we need to combine all their Hilbert spaces into one bigger Hilbert space.

Mathematically, that means that if we have a Hilbert space H and another Hilbert space J, we denote their tensor product as:

If H is an h dimensional space and J is a j dimensional space, then the dimension of the combined space M is h j. In other words:

Before we go any farther, let's look at the tensor product of two vectors.

The tensor product of vectors

The tensor product of two vectors is denoted in the following way in bra-ket notation. You'll notice that there are four different ways...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime