From qubits to algorithms, embark on the quantum computing journey shaping our future

Vover of Dancing with Qubits, Second EditionUnlock the core math and understand the technical nuances of quantum computing in this detailed guide. Delve into the practicality of NISQ algorithms, and survey promising advancements in quantum machine learning.

Key Features

  • Discover how quantum computing works and delve into the math behind it with practical examples
  • Learn about and assess the most up-to-date quantum computing topics, including quantum machine learning
  • Explore the inner workings of existing quantum computing technologies to understand how they may perform significantly better than their classical counterparts

Book Description

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.

What You Will Learn

  • Explore the mathematical foundations of quantum computing
  • Discover the complex, mind-bending concepts that underpin quantum systems
  • Understand the key ideas behind classical and quantum computing
  • Refresh and extend your grasp of essential mathematics, computing, and quantum theory
  • Examine a detailed overview of qubits and quantum circuits
  • Dive into quantum algorithms such as Grover’s search, Deutsch-Jozsa, Simon’s, and Shor’s
  • Explore the main applications of quantum computing in the fields of scientific computing, AI, and elsewhere

Who This Book Is For

Dancing with Qubits, Second Edition is a quantum computing textbook for all who want to understand and explore the inner workings of quantum computing. This entails building up from basic to some sophisticated mathematics and is therefore best suited for those with a healthy interest in mathematics, physics, engineering, or computer science.

Table of Contents

  1. Why Quantum Computing
  2. They’re Not Old, They’re Classics
  3. More Numbers than You Can Imagine
  4. Planes and Circles and Spheres, Oh My
  5. Dimensions
  6. What Do You Mean “Probably”?
  7. One Qubit
  8. Two Qubits, Three
  9. Wiring Up the Circuits
  10. From Circuits to Algorithms
  11. Getting Physical
  12. Considering NISQ Algorithms
  13. Introduction to Quantum Machine Learning
  14. Questions about the Future

Corrections

Production Reference Section Page (PDF and Printed) Original Text New Text
1250324 1.4 15 The plot in Figure 1.9 is an example of a line separating the dark gray points below from the light gray ones above. The plot in Figure 1.9 is an example of a line separating the dark gray points above from the light gray ones below.
1250324 3.2 63 The definition means that $w^1=1$. The definition means that $w^1=w$.
1250324 3.5.3 86 The binary expansion of the decimal 5.125 is ${110.001}_2$, for example. The binary expansion of the decimal 5.125 is ${101.001}_2$, for example.
1250324 3.5.4 91 We can approximate r as closely as we wish by computing a divergent … We can approximate r as closely as we wish by computing a convergent …
1250324 3.9.3 105 $e^{\pi i} = -1$ or $e^{\pi i} – 1 = 0$ $e^{\pi i} = -1$ or $e^{\pi i} + 1 = 0$
1250324 5.10 211 The diagonal entries are none other than the eigenvalues with the orthonormal basis
as eigenvalues.		 The diagonal entries are none other than the eigenvalues with the orthonormal basis
as eigenvectors.
1250324 7.2 252 $${\left| {v} \middle> \middle< {w} \right|} =
\begin{bmatrix}
3(2 – i) & 3 \times 4 \\
i(2 – i) & i \times 4
\end{bmatrix}
=
\begin{bmatrix}
6 – 3i & 12 \\
1 + 2i & 4i
\end{bmatrix}$$		 $${\left| {v} \middle> \middle< {w} \right|} =
\begin{bmatrix}
3(2 – i) & 3 \times 4 \\
-i(2 – i) & -i \times 4
\end{bmatrix}
=
\begin{bmatrix}
6 – 3i & 12 \\
1 – 2i & -4i
\end{bmatrix}$$