Quantum AI Systems: Theory, Architecture, and Applications presents a comprehensive systems-level framework for integrating quantum information science, artificial intelligence, systems engineering, and governance into deployable intelligent architectures.
Rather than treating quantum computing as an isolated accelerator, this work introduces Quantum AI Systems (QAIS) as a system-of-systems discipline where representation, inference, learning, communication, sensing, optimization, deployment, and governance operate within a unified architectural framework.
The book develops the dual evaluative frameworks of QALIS and CRQC-LLM, demonstrating how identical technical capabilities can produce either resilient, trustworthy outcomes or fragile, failure-prone systems depending on architectural design and governance choices.
Across thirteen chapters, readers progress from foundational quantum information concepts through quantum reasoning, learning architectures, optimization, communication systems, sensing infrastructures, deployment architectures, and long-horizon governance considerations.
Designed for students, researchers, engineers, cybersecurity professionals, AI practitioners, and technology leaders, the text emphasizes operational realism, verification, resilience, interpretability, and responsible deployment of advanced intelligent systems.
Companion laboratories, instructional resources, and supplemental materials are available through QuSciTech Labs.
