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Quantum computing : an environment for intelligent large scale real application
Hassanien A., Elhoseny M., Kacprzyk J., Springer International Publishing, New York, NY, 2018. 505 pp. Type: Book (978-3-319636-38-2)
Date Reviewed: Nov 26 2018

The book covers applications in quantum computing, along with some fundamental research. The application areas include cryptography, networking, image processing, optimization, and multi-user systems. The research work includes quantum field theory computers, algorithms, and uncertainty propagation.

The book is organized in three parts. The first part is on quantum-computing-based cryptology. The first chapter introduces private key distribution protocols such as BB84 and E91. It also introduces direct communication protocols such as the Deng protocol. Chapter 2 describes various ways in which quantum computing is applied in secure communication, for example, satellite-based communications protocols. Chapter 3 discusses different types of architectures for quantum key distribution networks. It explains quantum backbone node-based networking and grids, and discusses in detail entangle-based secure network communications. Chapter 4 describes the fundamentals of quantum cryptography, explaining quantum bits, quantum bit gates, entanglement, the no-cloning theorem, quantum-based dense coding, algorithms for secure transmission, and group key management. Chapter 5 is on point-to-multipoint communication. It describes various general architectures for quantum key distribution on such systems. The architectural approaches include layered approaches. Chapter 6 describes the Internet protocol security (IPsec) model with quantum computing. The description includes the architecture, processes, and phases involved. Chapter 7 is on quantum server design and cooperation among users. Chapter 8 presents an algorithm for quantum key distributions in noisy environments. Chapter 9 introduces some basics on video streaming over wireless networks.

The second part relates to physics. Chapter 10 describes quantum field theory computers. It claims that NP problems can be done in polynomial time on such computers. Chapter 11 describes a new algorithm for uncertainty propagation in quantum physics using what it calls negative probabilities. Chapter 12 discusses no-hidden-variables theorems and hidden-variable theory. Chapter 13 describes the fundamentals of quantum-based memory. Chapters 14 and 15 discuss neural networks and quantum computing with respect to each other, noting the basic differences and similarities between them.

Part 3 is on quantum computing applications in artificial intelligence (AI) problems. Chapter 16 gives a quantum-inspired genetic algorithm. The algorithm is applied to a thermal power station application. Chapter 17 describes a particle swam optimization (PSO) algorithm. The algorithm is applied to a distributed power generation application. Chapter 18 proposes an algorithm for automatic face detection. Chapter 19 describes a method for automatic aerial systems. Chapter 20 describes an application in medical image watermarking. Chapter 21 applies quantum-based swarm optimization in power optimization applications such as load forecasting.

The first part is mostly informative. Engineers who are studying/working in network security will benefit from reading it. It can also be used in an undergraduate course. Understanding Part 2 requires a strong background in quantum physics, mathematics, and computer science. The book, in general, can be used for studying quantum computing at various levels.

Reviewer:  Maulik A. Dave Review #: CR146327 (1902-0012)
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