量子计算：讲义
Quantum Computing: Lecture Notes
AI总结：
本研究是一套面向硕士阶段的量子计算课程讲义，从理论计算机科学视角覆盖量子算法、复杂性理论等多领域内容，配套习题与背景知识附录。
摘要：
这是一套适合从理论计算机科学视角开设的量子计算与量子信息硕士课程的讲义。首版撰写于2011年，后续数年经过大量扩充与修订。前10章涵盖量子电路模型及主要量子算法，包括Deutsch-Jozsa算法、Simon算法、Shor算法、隐子群问题（Hidden Subgroup Problem）、Grover算法、量子行走、哈密顿量模拟以及HHL算法。其后是4章关于量子复杂性理论的内容、4章关于分布式（“Alice与Bob”）场景的内容，还有一章关于量子机器学习、一章关于稳定子态与Clifford电路，最后一章讲解量子纠错。附录A和B简要介绍所需的线性代数及其他数学与计算机科学背景知识。所有章节均配有习题，部分提示见附录C。
英文摘要：
This is a set of lecture notes suitable for a Master's course on quantum computation and information from the perspective of theoretical computer science. The first version was written in 2011, with many extensions and improvements in subsequent years. The first 10 chapters cover the circuit model and the main quantum algorithms (Deutsch-Jozsa, Simon, Shor, Hidden Subgroup Problem, Grover, quantum walks, Hamiltonian simulation and HHL). They are followed by 4 chapters about complexity, 4 chapters about distributed ("Alice and Bob") settings, a chapter about quantum machine learning, one about stabilizer states and Clifford circuits, and a final chapter about quantum error correction. Appendices A and B give a brief introduction to the required linear algebra and some other mathematical and computer science background. All chapters come with exercises, with some hints provided in Appendix C.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
