Overview
- Expanded coverage of quantum machine learning and quantum error correction
- Best selling book giving hands-on instruction to quantum computing
- Companion website with code, problem sets and additional resources
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Keywords
- Quantum computing
- Quantum computers
- Quantum computation
- Superconducting qubits
- Qubits
- Quantum supremacy
- Quantum advantage
- Bristlecone
- IBM quantum
- Trapped ion
- Cirq
- QISkit
- Q#
- Shor’s algorithm
- Grover’s algorithm
- Quantum optimization
- Quantum machine learning
- Quantum AI
- probability density function
- Borne Rule
About this book
This book integrates the foundations of quantum computing with a hands-on coding approach to this emerging field; it is the first to bring these elements together in an updated manner. This work is suitable for both academic coursework and corporate technical training.
The second edition includes extensive updates and revisions, both to textual content and to the code. Sections have been added on quantum machine learning, quantum error correction, Dirac notation and more. This new edition benefits from the input of the many faculty, students, corporate engineering teams, and independent readers who have used the first edition.
This volume comprises three books under one cover: Part I outlines the necessary foundations of quantum computing and quantum circuits. Part II walks through the canon of quantum computing algorithms and provides code on a range of quantum computing methods in current use. Part III covers the mathematical toolkit required to master quantum computing. Additional resources include a table of operators and circuit elements and a companion GitHub site providing code and updates.
Jack D. Hidary is a research scientist in quantum computing and in AI at Alphabet X, formerly Google X.
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Authors and Affiliations
About the author
Jack D. Hidary focuses on AI and on quantum computing at Alphabet X, formerly Google X. He and his group develop and research algorithms for NISQ-regime quantum processors as well as create new software libraries for quantum computing. In the AI field, Jack and his group focus on fundamental research such as the generalization of deep networks as well as applied AI technologies.
Bibliographic Information
Book Title: Quantum Computing: An Applied Approach
Authors: Jack D. Hidary
DOI: https://doi.org/10.1007/978-3-030-83274-2
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-83273-5Published: 03 November 2021
eBook ISBN: 978-3-030-83274-2Published: 29 September 2021
Edition Number: 2
Number of Pages: XXIII, 422
Number of Illustrations: 20 b/w illustrations, 46 illustrations in colour
Topics: Quantum Computing, Professional Computing, Quantum Physics