| Course code | CSCI5370 |
| Course title | Quantum Computing 量子計算 |
| Course description | This course provides an introduction to the following topics in quantum computation: 1. Models of quantum computation and communication; 2. Quantum algorithms and their limitations; 3. Other topics (quantum communication, quantum cryptography, quantum proofs, quantum error correction, quantum supremacy). 本科介紹量子計算中的以下主題：1. 量子計算與通信模型；2. 量子算法及其局限性；3. 其他主題（量子通信，量子密碼學，量子證明，量子糾錯，量子優越性）。 |
| Unit(s) | 3 |
| Course level | Postgraduate |
| Semester | 1 or 2 |
| Grading basis | Graded |
| Grade Descriptors | A/A-: EXCELLENT – exceptionally good performance and far exceeding expectation in all or most of the course learning outcomes; demonstration of superior understanding of the subject matter, the ability to analyze problems and apply extensive knowledge, and skillful use of concepts and materials to derive proper solutions. B+/B/B-: GOOD – good performance in all course learning outcomes and exceeding expectation in some of them; demonstration of good understanding of the subject matter and the ability to use proper concepts and materials to solve most of the problems encountered. C+/C/C-: FAIR – adequate performance and meeting expectation in all course learning outcomes; demonstration of adequate understanding of the subject matter and the ability to solve simple problems. D+/D: MARGINAL – performance barely meets the expectation in the essential course learning outcomes; demonstration of partial understanding of the subject matter and the ability to solve simple problems. F: FAILURE – performance does not meet the expectation in the essential course learning outcomes; demonstration of serious deficiencies and the need to retake the course. |
| Learning outcomes | At the end of the course of studies, students will 1. understand the power and limitations of quantum computation; 2. be able to program a quantum computer; 3. be able to use and modify existing quantum algorithms in computational applications. |
| Assessment (for reference only) |
Presentation: 40% Homework or assignment: 30% Test or quiz: 30% |
| Recommended Reading List | 1. Ronald de Wolf. Quantum computing: Lecture notes. https://homepages.cwi.nl/~rdewolf/qcnotes.pdf 2. N. David Mermin. Quantum computer science: An introduction. Cambridge Univ. Press, 2007 3. Michael A. Nielsen and Isaac R. Chuang. Quantum computation and quantum information. Cambridge Univ. Press, 2011 4. Scott Aaronson. Quantum computing since Democritus. Cambridge Univ. Press, 2013 |
| CSCIN programme learning outcomes | Course mapping |
| Upon completion of their studies, students will be able to: | |
| 1. identify, formulate, and solve computer science problems (K/S); | |
| 2. design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs (K/S); |
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| 3. receive the broad education necessary to understand the impact of computer science solutions in a global and societal context (K/V); | |
| 4. communicate effectively (S/V); |
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| 5. succeed in research or industry related to computer science (K/S/V); |
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| 6. have solid knowledge in computer science and engineering, including programming and languages, algorithms, theory, databases, etc. (K/S); | |
| 7. integrate well into and contribute to the local society and the global community related to computer science (K/S/V); | |
| 8. practise high standard of professional ethics (V); | |
| 9. draw on and integrate knowledge from many related areas (K/S/V); |
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| Remarks: K = Knowledge outcomes; S = Skills outcomes; V = Values and attitude outcomes; T = Teach; P = Practice; M = Measured | |