Book Image

Essential Mathematics for Quantum Computing

By : Leonard S. Woody III
5 (1)
Book Image

Essential Mathematics for Quantum Computing

5 (1)
By: Leonard S. Woody III

Overview of this book

Quantum computing is an exciting subject that offers hope to solve the world’s most complex problems at a quicker pace. It is being used quite widely in different spheres of technology, including cybersecurity, finance, and many more, but its concepts, such as superposition, are often misunderstood because engineers may not know the math to understand them. This book will teach the requisite math concepts in an intuitive way and connect them to principles in quantum computing. Starting with the most basic of concepts, 2D vectors that are just line segments in space, you'll move on to tackle matrix multiplication using an instinctive method. Linearity is the major theme throughout the book and since quantum mechanics is a linear theory, you'll see how they go hand in hand. As you advance, you'll understand intrinsically what a vector is and how to transform vectors with matrices and operators. You'll also see how complex numbers make their voices heard and understand the probability behind it all. It’s all here, in writing you can understand. This is not a stuffy math book with definitions, axioms, theorems, and so on. This book meets you where you’re at and guides you to where you need to be for quantum computing. Already know some of this stuff? No problem! The book is componentized, so you can learn just the parts you want. And with tons of exercises and their answers, you'll get all the practice you need.
Table of Contents (20 chapters)
1
Section 1: Introduction
4
Section 2: Elementary Linear Algebra
8
Section 3: Adding Complexity
13
Section 4: Appendices
Appendix 1: Bra–ket Notation
Appendix 2: Sigma Notation
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:

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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...