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

Linear independence

So, it ends up that these vectors got together and wrote a declaration of independence and that's what we'll cover here. Just joking! We do need humor every so often in a math book. To explain linear independence, we need to go back to the concept of a linear combination that we introduced earlier in this book.

Linear combination

We learned in Chapter 2, Superposition with Euclid, that linear combinations are the scaling and addition of vectors. I would like to give a more precise definition as we go beyond three-dimensional space.

A linear combination for vectors |x1,|x2, … |xn and scalars c1, c2, … cn in a vector space, V, is a vector of the form:

(1)

Basically, it is still scaling and addition, but now we can do it for vectors of any dimension and with as many finite numbers of vectors as we wish.

Let's look at an example:

So now that we have defined linear combinations, let...

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