Quantum Machine Learning (QML): Platform, Tools and Applications (Advances in Computers)

Kim, Shiho (EDT)/ Deka, Ganesh Chandra (EDT)

Academic Press Inc（2026/02発売）

• 製本 Hardcover:ハードカバー版／ページ数 314 p.
• 言語 ENG
• 商品コード 9780443223822
• DDC分類 006.31

Full Description

Quantum Machine Learning (QML): Platform, Tools and Applications, Volume 140 in the Advances in Computers series, explores the intersection of quantum computing and artificial intelligence, highlighting advances that promise to revolutionize computational science. The book introduces foundational concepts in quantum computing and circuits, building toward the practical implementation of quantum machine learning (QML) algorithms. Chapters address challenges such as the gradient vanishing problem in variational quantum circuits and explore powerful optimization methods enabled by quantum mechanics. The volume also covers advanced applications, including quantum approaches to smart grid management, quantum Monte Carlo simulations, and predictive modeling in numerical solvers using quantum neural networks.

Real-world relevance is underscored through discussions of transformative quantum algorithms and their potential to reshape machine learning, enabling unprecedented performance in data analysis, optimization, and beyond.

Contents

1. Introduction to Quantum Machine Learning (QML)
2. Quantum Computing Basics
3. Basic circuits for Quantum Computations
4. Quantum Machine Learning
5. Addressing the Gradient Vanishing Problem in Parametrized Quantum Circuit Training and Optimization
6. Quantum Optimization techniques and applications
7. Next-Gen Smart Grids: A Quantum Approach
8. Quantum Monte Carlo simulations
9. QPDE - Quantum Neural Network Based Stabilization Parameter Prediction for Numerical Solvers for Partial Differential Equations
10. Transforming Machine Learning: An In-Depth Exploration of Quantum Algorithms and Their Applications