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Nº de artículo:
87910452
Quantum Computing: An Applied Approach
85% of respondents would recommend this to a friend
Nº de artículo:
87910452
HNL 1425
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This book integrates the foundations of quantum computing with a hands-on coding approach to this emerging field
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What Stands Out
Practical Framework
Offers an applied approach, enabling readers to grasp complex quantum concepts through real-world examples, making it ideal for professionals and students alike.
Comprehensive Coverage
Covers a wide array of quantum computing topics, ensuring a solid foundation for both beginners and experienced readers, addressing the growing demand for quantum knowledge.
Author Expertise
Written by industry leaders, providing insights backed by extensive research and hands-on experience, enhancing the learning experience for those seeking detailed understanding.
Detalles de producto
- 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.
| Publisher | Springer |
| Publication date | 3 Nov. 2021 |
| Edition | Second Edition 2021 |
| Language | English |
| Print length | 445 pages |
| ISBN-10 | 3030832732 |
| ISBN-13 | 978-3030832735 |
| Item weight | 907 g |
| Dimensions | 15.88 x 2.54 x 24.13 cm |
Who Should Buy?
-
Students of Computing
Ideal for undergraduate or graduate students pursuing knowledge in quantum computing and advanced algorithms.
-
Industry Professionals
Great for professionals in tech industries looking to apply quantum computing solutions to real-world problems.
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Researchers and Academics
Suitable for researchers seeking practical approaches and methodologies in quantum computing for their studies.
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Casual Enthusiasts
Not suitable for casual readers lacking a background in computer science or quantum mechanics.
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Preguntas y respuestas de los clientes
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Pregunta:
Who is the author of the book?
Respuesta: Jack D. Hidary -
Pregunta:
What topics are covered in the second edition?
Respuesta: Quantum machine learning, quantum error correction, Dirac notation, and more. -
Pregunta:
What resources are provided with the book?
Respuesta: A table of operators and circuit elements and a companion GitHub site providing code and updates.
Higher Education Editorial Review
** Quantum Computing: An Applied Approach** "Quantum Computing: An Applied Approach," authored by Jack Hidary, has garnered attention for its comprehensive and updated exploration of quantum computing (QC) technology. The book's recent second edition enhances the original by including significant developments in the field, making it an indispensable resource both for novices and experts alike. One of its most commendable features is its ability to cater to readers from diverse backgrounds through its multi-faceted structure, which divides the content into three main sections: Foundations, Hardware and Applications, and Toolkits. Readers have expressed appreciation for the author’s clear guidance and structured learning paths tailored to different audiences—such as university instructors, physicists, software programmers, and business leaders. The self-test in the math section is particularly highlighted as a practical tool, allowing readers to gauge their understanding before diving deeper into the math necessary for QC. Moreover, feedback indicates that the book is refreshingly up-to-date, a vital trait in the rapidly evolving realm of quantum computing, where advances can render information obsolete within months. The book's ability to stay current is augmented by its dedicated GitHub site, offering readers ongoing access to learning resources and the latest tech updates. Notably, the expansion in areas like Quantum Machine Learning and Quantum Error Correction provides additional layers of value, ensuring that even returning readers benefit from the enhancements found in the second edition. However, the book is not without some complaints. One reader noted difficulties with Kindle compatibility, which may limit accessibility for some potential users. Yet, overall, the reception highlights that "Quantum Computing: An Applied Approach" is an essential read for anyone looking to grasp the intricate but crucial advances in quantum computing. **
Customer Reviews & Ratings
153 valoraciones de los clientes
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ventajas
- Comprehensive structure catering to various backgrounds.
- Up-to-date content reflecting recent advancements in QC.
- Clear learning paths recommended for different reader categories.
- Practical self-test in the math section to assess understanding.
- Includes significant new content in the second edition.
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características y beneficios
- Integrates foundations of quantum computing with hands-on coding approach
- Suitable for academic coursework and corporate technical training
- Extensive updates and revisions in the second edition
- Includes sections on quantum machine learning, quantum error correction, and Dirac notation
- Comprises three books in one volume
- Additional resources include a table of operators and circuit elements and a companion GitHub site providing code and updates
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