Details derivations and implementations of over 50 fundamental quantum algorithms and techniques, including Shor's and Grover's algorithms, Fourier transforms, quantum teleportation and QML, all simulated in Python. Precise yet easy-to-understand mathematics and over 120 illustrations make this a quintessential book for learning quantum computing.
Details derivations and implementations of over 50 fundamental quantum algorithms and techniques, including Shor's and Grover's algorithms, Fourier transforms, quantum teleportation and QML, all simulated in Python. Precise yet easy-to-understand mathematics and over 120 illustrations make this a quintessential book for learning quantum computing.
Robert Hundt is a Google Distinguished Engineer, leading system software development for Google's TPU machine-learning supercomputers, including the XLA compiler for TPU, GPU and CPU. He also worked on an open-source CUDA compiler and the high-level synthesis toolchain XLS. He has over twenty-five scientific publications, holds thirty-eight patents, and is a senior member of IEEE.
Inhaltsangabe
Acknowledgments Introduction 1. The mathematical minimum 2. Quantum computing fundamentals 3. Simulation infrastructure 4. Quantum tools and techniques 5. Beyond classical 6. Algorithms exploiting entanglement 7. State similarity tests 8. Black-box algorithms 9. State preparation 10. Algorithms using amplitude amplification 11. Algorithms using quantum Fourier transformation 12. Quantum walk algorithms 13. Optimization algorithms 14. Quantum machine learning 15. Quantum error correction 16. Quantum languages, compilers, and tools Appendix: Sparse implementation.