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Overview: 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. Quantum computing is an elegant fusion between computer science and principles of quantum physics to facilitate calculations. It promises an excellent computational capacity that is intractable for classical computers to solve challenging problems, including materials science, information science, computer science, mathematical science, and others. The QB SDK is designed for ease of integration into a range of performance-critical environments: HPC, cloud, GPU workstations and even embedded/edge systems. The SDK’s high-performance core and bundled simulators are implemented in C++. It provides hybrid and pure-quantum programming interfaces in both C++ and Python, with an extensive language binding module for Python included.
Genre: Non-Fiction > Tech & Devices
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