Postgraduate Course: Introduction to Quantum Computing (INFR11099)

Course Outline
School	School of Informatics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 11 (Year 4 Undergraduate)	Availability	Available to all students
SCQF Credits	10	ECTS Credits	5
Summary	The aim of this course is to give students a basic overview of the rapidly growing field of Quantum Computation (QC). The course will start with a brief introduction of the mathematical framework of QC. The two models of quantum circuit and measurement-based quantum computing, will be introduced. Through these models various key concepts in QC such as entanglement and teleportation will be discussed. In order to compare QC and classical computing, simple quantum algorithms with their complexity analysis will be presented. We finish the course by highlighting the recent development of the field in secure delegated QC.
Course description	- Basic concepts from Linear Algebra necessary for understanding the axioms of Quantum Mechanics, - Axioms of Quantum Mechanics, describing quantum system, quantum operators, composition, entanglement and measurements - The no cloning, no deleting theorems and the consequences for computation - Quantum Computing via quantum circuit model: Description of qubit and universal set of gates. - Quantum space and depth complexity and oracle model - Classical simulation of quantum circuit and Gottesman-Knill Theorem - Quantum Algorithms: Groverżs Search and Deutsch-Jozsa problem - The first quantum protocols: Quantum teleportation and super dense coding - Quantum Computing via measurement-based model: Description of graph state and measurement calculus - Advanced Topics: Information flow in measurement-based model, unconditionally secure quantum cloud computing

Entry Requirements (not applicable to Visiting Students)
Pre-requisites	Students MUST have passed: ( Quantum Mechanics (PHYS09053) OR Principles of Quantum Mechanics (PHYS10094)) OR ( Introduction to Linear Algebra (MATH08057) AND Probability with Applications (MATH08067))	Co-requisites
Prohibited Combinations		Other requirements	This course is open to all Informatics students including those on joint degrees. For external students where this course is not listed in your DPT, please seek special permission from the course organiser. Basic knowledge of linear algebra, vector spaces, probability theory, complex numbers, models of computation, computability and intractability. Undergraduate students must have passed either Quantum Mechanics or both Introduction to Linear Algebra and Probability with Applications. Postgraduate or visiting students must have taken similar courses providing this background in their undergraduate degrees. No programming experience is required.

Information for Visiting Students
Pre-requisites	Visiting students are required to have comparable background to that assumed by the course prerequisites listed in the Degree Regulations & Programmes of Study. If in doubt, consult the course lecturer.
High Demand Course?	Yes

Course Delivery Information

Academic year 2017/18, Available to all students (SV1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 100 ( Lecture Hours 20, Seminar/Tutorial Hours 8, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 68 )
Assessment (Further Info)	Written Exam 90 %, Coursework 10 %, Practical Exam 0 %
Additional Information (Assessment)	You should expect to spend approximately 12 hours on the coursework for this course. If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Feedback	Not entered
Exam Information
Exam Diet	Paper Name		Hours & Minutes
Main Exam Diet S2 (April/May)			2:00

Academic year 2017/18, Part-year visiting students only (VV1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 100 ( Lecture Hours 20, Seminar/Tutorial Hours 8, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 68 )
Assessment (Further Info)	Written Exam 90 %, Coursework 10 %, Practical Exam 0 %
Additional Information (Assessment)	You should expect to spend approximately 12 hours on the coursework for this course. If delivered in semester 1, this course will have an option for semester 1 only visiting undergraduate students, providing assessment prior to the end of the calendar year.
Feedback	Not entered
Exam Information
Exam Diet	Paper Name		Hours & Minutes
Main Exam Diet S1 (December)			2:00

Learning Outcomes
On completion of this course, the student will be able to: Use the mathematical framework of quantum computing to solve computational problems Critically read and understand scientific papers on quantum computing Explain and analyse any quantum algorithms described in quantum circuit or measurement-based quantum computing models Relate quantum complexity classes to the classical ones Gain experience in problem solving for complex system

Reading List
The principal source will be lectures slides provided during the course. Other textbook for the course are "Quantum Computation and Quantum Information" by Nielsen and Chuang, "An Introduction to Quantum Computing" by Kaye, Laflamme and Mosca. Also a useful supporting textbook for the course is "Quantum Information" by Stephen Barnett.

Additional Information
Course URL	http://course.inf.ed.ac.uk/iqc
Graduate Attributes and Skills	Ability to analyse complex system and to design syntaxes to capture computational phenomena, familiarity with information encoding in natural system and distinguishing the boundary between classical and physical computation.
Keywords	Not entered