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Quantum Machine Learning: Concepts and possibilities (IOP Series in Quantum Technology)

Physics

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Description

The scope of the book spans from the fundamental postulates of quantum mechanics and quantum algorithms that underpin QML, to advanced topics including variational quantum algorithms, quantum neural networks, and quantum generative models. It covers both the theoretical formulations, such as expressivity, generalization bounds, and kernel methods, and practical applications, ranging from optimization and pattern recognition to simulation and sensing. The text also explores hybrid quantum-classical workflows, error mitigation strategies, and benchmarks that connect algorithmic development to near-term hardware implementations. By the end of this book, readers gain a holistic view of the current state, promises, and challenges of QML, as well as directions for future research in this rapidly evolving field. Key Features: A chapter on quantum generative models. Accessible reference text useful for both students and researchers. Case studies

Product Specifications

Format: hardcover
ASIN: 0750349506
Category: Books > Subjects > Science, Nature & Maths > Popular Science > Physics
Domain: Amazon UK
Release Date: 15 December 2025
Listed Since: 26 October 2021

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Quantum Machine Learning: Concepts and possibilities (IOP Series in Quantum Technology)

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