Hamilton K Quantum Machine Learning Concepts and possibilities 2025
General:
Name: Hamilton K Quantum Machine Learning Concepts and possibilities 2025
Format: pdf
Size: 7.34 MB
Book:
Title: Quantum Machine Learning: Concepts and possibilities
Author: Kathleen E. Hamilton, Andrea Delgado
Language: angielski
Year: 2025
Subjects: N/A
Publisher: Institute of Physics Publishing
ISBN: 9780750349529
Total pages: 135
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
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