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 3 chapters about complexity, 4 chapters about distributed ("Alice and Bob") settings, a chapter about quantum machine learning, 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.
翻译：这是一套适合从理论计算机科学角度进行量子计算和信息硕士课程的讲解说明,第一版于2011年编写,在随后几年有许多扩展和改进,前十章涵盖电路模型和主要量子算法(Deutsch-Jozsa、Simon、Shor、隐藏的分组问题、Grover、量子漫步、汉密尔顿模拟和HHL),随后有3章涉及复杂性,4章涉及分布式设置(“爱丽丝和鲍勃”),1章涉及量子机器学习,1章涉及量子机器学习,1章涉及量子错误纠正。附录A和B简要介绍了所需的直线代数以及其他一些数学和计算机科学背景。所有章节都有练习,附录C提供了一些提示。
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