Quantum Computing: Circuits, Systems, Automation and Applications

This book provides readers with the current state-of-the-art research and technology on quantum computing. The authors provide design paradigms of quantum computing. Topics covered include multi-programming mechanisms on near-term quantum computing, Lagrange interpolation approach for the general parameter-shift rule, architecture-aware decomposition of quantum circuits, software for massively parallel quantum computing, machine learning in quantum annealing processors, quantum annealing for real-world machine learning applications, queuing theory models for (Fault-Tolerant) quantum circuits, machine learning for quantum circuit reliability assessment, and side-channel leakage in Suzuki stack circuits.