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Dancing with Qubits

Dancing with Qubits

By : Robert S. Sutor
5 (24)
close
Dancing with Qubits

Dancing with Qubits

5 (24)
By: Robert S. Sutor

Overview of this book

Dancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. A full description of classical computing and the mathematical underpinnings of quantum computing follows, helping you better understand concepts such as superposition, entanglement, and interference. Next up are circuits and algorithms, both basic and sophisticated, as well as a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments may affect you. This new edition is updated throughout with more than 100 new exercises and includes new chapters on NISQ algorithms and quantum machine learning. Understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is explained thoroughly and with helpful examples, leaving you with a solid foundation of knowledge in quantum computing that will help you pursue and leverage quantum-led technologies.
Table of Contents (26 chapters)
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1
I Foundations
8
II Quantum Computing
14
III Advanced Topics
18
Afterword
22
Other Books You May Enjoy
23
References
24
Index
Appendices

5.3 Linear maps

We’ve looked at linear functions several times to get a concrete idea of how they work. We must generalize this idea to vector spaces.

Let U and V be vector spaces over the same field F. Let u1 and u2 be in U and s1 and s2 be scalars in F.

The function L: UV is a linear map if

Displayed math

In particular, we have

Displayed math

When U = V, we also say L is a linear transformation of U or a linear operator on U. linear$map linear$transformation linear$operator

All linear transformations on R2 look like

Displayed math

using Cartesian coordinates, and with a, b, c, d, x, and y in R. This is interesting because the linear transformations on R1 all look like the somewhat trivial xax.

Exercise 5.2

Show that the function

Displayed math

for a, b, c, d, x, and y in C is a linear transformation of C2.

The linear transformations on R3...

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