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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

Representing linear transformations with matrices

Now for the most common and important way of describing a linear transformation, the matrix. Through the magic of matrix-vector multiplication, a matrix is all you need to describe a linear transformation.

Again, let's start with an example. I'm going to describe the linear transformation we used in the An algebraic description section with a matrix. To jog your memory, here is the aforementioned linear transformation:

Now, here is how I can describe it with a matrix:

I don't even need to be that formal, other than telling you that we are using real numbers; I can just give you the matrix, and that describes everything. The dimension of the domain is the number of columns of the matrix, the dimension of the codomain is the number of rows of the matrix, and the actual transformation is the matrix itself. That is the power of a matrix!

Let's apply this transformation...

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