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Dancing with Qubits

You're reading from   Dancing with Qubits From qubits to algorithms, embark on the quantum computing journey shaping our future

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781837636754
Length 684 pages
Edition 2nd Edition
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Author (1):
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Robert S. Sutor Robert S. Sutor
Author Profile Icon Robert S. Sutor
Robert S. Sutor
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Table of Contents (26) Chapters Close

Preface I Foundations
Why Quantum Computing FREE CHAPTER They’re Not Old, They’re Classics More Numbers Than You Can Imagine Planes and Circles and Spheres, Oh My Dimensions 6 What Do You Mean “Probably”? II Quantum Computing
One Qubit Two Qubits, Three Wiring Up the Circuits From Circuits to Algorithms Getting Physical III Advanced Topics
Considering NISQ Algorithms Introduction to Quantum Machine Learning Questions about the Future Afterword
A Quick Reference B Notices C Production Notes Other Books You May Enjoy
References
Index
Appendices

8.1 Tensor products

In this section, I introduce the linear algebra construction of a tensor product. If the direct sum seems to concatenate two vector spaces, then the tensor product interleaves them. In the first case, if we start with dimensions n and m, we end up with a new vector space of n + m dimensions. For the tensor product, we get nm dimensions. linear$algebra product$tensor product$Kronecker Kronecker$product tensor product vector space$tensor product vector space$Kronecker product

We can quickly get vector spaces with high dimensions through this multiplicative effect. We must use our algebraic intuition and tools more than our geometric ones.

The initial construction is straight linear algebra, but we specialize it later to quantum computing and working with multiple qubits.

Vector spaces

Let V and W be two finite-dimensional vector spaces over F. We define a new vector space VW, pronounced “V tensor W...

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