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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

The inverse of a matrix

It would be nice to have a way to do algebra on matrices the way we do for simple algebraic expressions, like so:

The inverse of a matrix provides us with a way to do this. It is very similar to the reciprocal for rational numbers. For rational numbers, the following is true:

In a similar way, the inverse of a matrix is defined to be a matrix that when multiplied by the original matrix, you get the identity matrix. Here it is mathematically:

The matrix inverse can then be used when trying to algebraically modify a matrix equation. Let's say we are trying to find the vector |x⟩ in the following equation:

Since we now have a multiplicative inverse of a matrix, we can multiply both sides by it to get the following:

Please remember that matrix multiplication is not commutative, so if you left multiply a matrix on one...

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