Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers.
This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. List of contributors - p. xi 7. About the editors - p. xv 8. Preface - p. xvii 9. Part 1: Vision and applications - p. 1 10. Chapter 1. Quantum computing at a glance - p. 3 11. Chapter 2. Quantum computing: vision and challenges - p. 19 12. Chapter 3. Quantum simulations and classical hybrid machine learning - p. 43 13. Chapter 4. Post quantum cryptography for data safeguarding - p. 69 14. Part 2: Architecture, systems and services - p. 81 15. Chapter 5. Quantum annealing for enhanced efficiency in high-frequency trading leveraging quantum cloud computing - p. 83 16. Chapter 6. Application of neural networks in lattice based cryptography - p. 97 17. Chapter 7. Hybrid quantum-classical framework for clustering - p. 115 18. Chapter 8. Quantum Serverless paradigm and application development using the QFaaS framework - p. 139 19. Chapter 9. QSimPy: A learning-centric simulation framework for quantum cloud resource management - p. 165 20. Part 3: New trends and emerging topics - p. 185 21. Chapter 10. Quantum-inspired resource management in wireless networks - p. 187 22. Chapter 11. Quantum machine learning: current trends and applications - p. 201 23. Chapter 12. Top research priorities in quantum computing - p. 221 24. Index - p. 241
Quantum Computing: Principles and Paradigms covers a broad range of topics, providing a state-of-the-art and comprehensive reference for the rapid progress in the field of quantum computing and related technologies from major international companies (such as IBM, Google, Intel, Rigetti, Q-Control) and academic researchers. This book appeals to a broad readership, as it covers comprehensive topics in the field of quantum computing, including hardware, software, algorithms, and applications, with chapters written by both academic researchers and industry developers.
This book presents readers with the fundamental concepts of quantum computing research, along with the challenges involved in developing practical devices and applications.
1. Title of Book - p. i 2. Cover image - p. i 3. Title page - p. ii 4. Table of Contents - p. iii 5. Copyright - p. iii 6. List of contributors - p. xi 7. About the editors - p. xv 8. Preface - p. xvii 9. Part 1: Vision and applications - p. 1 10. Chapter 1. Quantum computing at a glance - p. 3 11. Chapter 2. Quantum computing: vision and challenges - p. 19 12. Chapter 3. Quantum simulations and classical hybrid machine learning - p. 43 13. Chapter 4. Post quantum cryptography for data safeguarding - p. 69 14. Part 2: Architecture, systems and services - p. 81 15. Chapter 5. Quantum annealing for enhanced efficiency in high-frequency trading leveraging quantum cloud computing - p. 83 16. Chapter 6. Application of neural networks in lattice based cryptography - p. 97 17. Chapter 7. Hybrid quantum-classical framework for clustering - p. 115 18. Chapter 8. Quantum Serverless paradigm and application development using the QFaaS framework - p. 139 19. Chapter 9. QSimPy: A learning-centric simulation framework for quantum cloud resource management - p. 165 20. Part 3: New trends and emerging topics - p. 185 21. Chapter 10. Quantum-inspired resource management in wireless networks - p. 187 22. Chapter 11. Quantum machine learning: current trends and applications - p. 201 23. Chapter 12. Top research priorities in quantum computing - p. 221 24. Index - p. 241
