Dancing with Qubits : From Qubits to Algorithms, Embark on the Quantum Computing Journey Shaping Our Future.

Format:

Book

Author/Creator:

Sutor, Robert S.

Series:

Expert insight.

Expert insight

Language:

English

Subjects (All):

Quantum computing.

Physical Description:

1 online resource (685 pages)

Edition:

2nd ed.

Place of Publication:

Birmingham : Packt Publishing, Limited, 2024.

System Details:

Mode of access: World Wide Web.

Biography/History:

Sutor Robert S. : Robert S. Sutor has been a technical leader and executive in the IT industry for over 40 years. More than two decades of that were spent in IBM Research in Yorktown Heights, New York USA. During his time there, he worked on and led efforts in symbolic mathematical computation, mathematical programming languages, optimization, AI, blockchain, and quantum computing. He is the author of Dancing with Qubits: How quantum computing works and how it can change the world and Dancing with Python: Learn Python software development from scratch and get started with quantum computing, also with Packt. He is the published co-author of several research papers and the book Axiom: The Scientific Computation System with the late Richard D. Jenks. Sutor was an IBM executive on the software side of the business in areas including Java web application servers, emerging industry standards, software on Linux, mobile, and open source. He was the Vice President of Corporate Development and, later, Chief Quantum Advocate, at Infleqtion, a quantum computing and quantum sensing company based in Boulder, Colorado USA. He is currently an Adjunct Professor in the Department of Computer Science and Engineering at the University at Buffalo, New York, USA. He is a theoretical mathematician by training, has a Ph. D. from Princeton University, and an undergraduate degree from Harvard College. He started coding when he was 15 and has used most of the programming languages that have come along.

Summary:

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.

Contents:

Intro

Copyright

Contributors

Contents

Preface

I Foundations

1 Why Quantum Computing

1.1 The mysterious quantum bit

1.2 I'm awake!

1.3 Why quantum computing is different

1.4 Applications to artificial intelligence

1.5 Applications to financial services

1.6 What about cryptography?

1.7 Summary

2 They're Not Old, They're Classics

2.1 What's inside a computer?

2.2 The power of two

2.3 True or false?

2.4 Logic circuits

2.5 Addition, logically

2.6 Algorithmically speaking

2.7 Growth, exponential and otherwise

2.8 How hard can that be?

2.9 Summary

3 More Numbers Than You Can Imagine

3.1 Natural numbers

3.2 Whole numbers

3.3 Integers

3.4 Rational numbers

3.5 Real numbers

3.6 Structure

3.7 Modular arithmetic

3.8 Doubling down

3.9 Complex numbers, algebraically

3.10 Summary

4 Planes and Circles and Spheres, Oh My

4.1 Functions

4.2 The real plane

4.3 Trigonometry

4.4 From Cartesian to polar coordinates

4.5 The complex ``plane''

4.6 Real three dimensions

4.7 Summary

5 Dimensions

5.1 R2 and C1

5.2 Vector spaces

5.3 Linear maps

5.4 Matrices

5.5 Matrix algebra

5.6 The determinant and trace

5.7 Length and preserving it

5.8 Unitary transformations

5.9 Change of basis

5.10 Eigenvectors and eigenvalues

5.11 Direct sums

5.12 Homomorphisms

5.13 Systems of linear equations

5.14 Summary

6 What Do You Mean ``Probably''?

6.1 Being discrete

6.2 More formally

6.3 Wrong again?

6.4 Probability and error detection

6.5 Randomness

6.6 Expectation

6.7 Hellinger distance

6.8 Markov and Chebyshev go to the casino

6.9 Summary

II Quantum Computing

7 One Qubit

7.1 Introducing quantum bits

7.2 Bras and kets

7.3 The complex math and physics of a single qubit.

7.4 A nonlinear projection

7.5 The Bloch sphere

7.6 Professor Hadamard, meet Professor Pauli

7.7 Gates and unitary matrices

7.8 Summary

8 Two Qubits, Three

8.1 Tensor products

8.2 Entanglement

8.3 Multi-qubit gates

8.4 The cat

8.5 Summary

9 Wiring Up the Circuits

9.1 So many gates

9.2 From gates to circuits

9.3 Building blocks and universality

9.4 Arithmetic

9.5 Welcome to Delphi

9.6 Amplitude amplification and interference

9.7 Searching with Grover

9.8 The Deutsch-Jozsa algorithm

9.9 The Bernstein-Vazirani algorithm

9.10 Simon's algorithm

9.11 Summary

10 From Circuits to Algorithms

10.1 Quantum Fourier Transform

10.2 Factoring

10.3 How hard can that be, again?

10.4 Phase kickback

10.5 Eigenvalue and phase estimation

10.6 Order and period finding

10.7 Shor's factoring algorithm

10.8 Summary

11 Getting Physical

11.1 That's not logical

11.2 What does it take to be a qubit?

11.3 Quantum cores and interconnects

11.4 Decoherence

11.5 Error correction for physical qubits

11.6 Quantum benchmarks

11.7 The software stack and access

11.8 Simulation

11.9 Light and photons

11.10 Summary

III Advanced Topics

12 Considering NISQ Algorithms

12.1 Cost functions and optimization

12.2 Heuristics

12.3 Hermitian matrices again

12.4 Expectation and the variational principle

12.5 Time evolution

12.6 Parameterized circuits

12.7 The Hamiltonian

12.8 Quantum approximate optimization algorithm (QAOA)

12.9 Is NISQ worth it?

12.10 Summary

13 Introduction to Quantum Machine Learning

13.1 What is machine learning?

13.2 Methods for encoding data

13.3 Quantum neural networks

13.4 Quantum kernels for SVMs

13.5 Other quantum machine learning research areas

13.6 Summary

14 Questions about the Future.

14.1 Ecosystem and community

14.2 Applications and strategy

14.3 Computing system access

14.4 Software

14.5 Hardware

14.6 Education

14.7 Workforce

14.8 Summary

Afterword

Appendices

A Quick Reference

A.1 One qubit kets

A.2 Two qubit kets

A.3 Pauli gates and matrices

A.4 Pauli strings of length 2

A.5 Greek letters

B Notices

B.1 Photos, images, and diagrams

B.2 Marks

B.3 Creative Commons Attribution-NoDerivs 2.0 Generic

B.4 Creative Commons Attribution-ShareAlike 2.0 Germany

B.5 Creative Commons Attribution 3.0 Unported

B.6 Creative Commons Attribution-ShareAlike 3.0 Unported

B.7 Los Alamos National Laboratory

B.8 Python 3 license

C Production Notes

C.1 How this book was built

C.2 Citing this book

C.3 Python version

C.4 LaTeX environment

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References

Index

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Notes:

Includes bibliographical references and index.

Description based on publisher supplied metadata and other sources.

ISBN:

9781837634620

1837634629

OCLC:

1429146908