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DRPS : Course Catalogue : School of Informatics : Informatics

Postgraduate Course: Introduction to Quantum Computing (INFR11099)

Course Outline
SchoolSchool of Informatics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 11 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryThe 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. We cover the most important quantum subroutines and their application to well-known quantum algorithms and compare their performance with respect to classical computing. We finish the course by surveying few more advanced topics, such as quantum error correction, algorithms for near-term architectures and 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
- Quantum Computing via quantum circuit model: Description of qubit and universal set of gates.
- The first quantum protocols: Quantum teleportation and super dense coding
- Quantum subroutines such as Phase Kick-back, Quantum Fourier Transform or Phase-Estimation
- Quantum Algorithms such as Grover's Search, Deutsch-Jozsa, Bernstein-Vazirani or Shor.
- Quantum Computing via measurement-based model: Description of graph state and measurement calculus
- Advanced Topics: quantum error correction, algorithm for near-term architectures, unconditionally secure quantum cloud computing
Entry Requirements (not applicable to Visiting Students)
Pre-requisites It is RECOMMENDED that students have passed ( Quantum Mechanics (PHYS09053) OR Principles of Quantum Mechanics (PHYS10094) OR Informatics Research Review (INFR11136) OR Research Methods in Security, Privacy, and Trust (INFR11188)) OR ( Introduction to Linear Algebra (MATH08057) AND Probability with Applications (MATH08067))
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-requisitesVisiting 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 2023/24, Available to all students (SV1) Quota:  None
Course Start Semester 1
Course Start Date 18/09/2023
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 75 %, Coursework 25 %, Practical Exam 0 %
Additional Information (Assessment) Exam 75%
Coursework 25%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Introduction to Quantum Computing (INFR11099)2:00
Learning Outcomes
On completion of this course, the student will be able to:
  1. use the mathematical framework of quantum computation to predict outcomes of quantum circuits
  2. explain and analyse quantum algorithms described in quantum circuit and measurement-based quantum computing models
  3. discuss the difference of performance between classical and quantum computer for different computational tasks
  4. master notions of more advanced topics, such as error correction on algorithms for near-term architectures
  5. critically read and understand scientific literature on quantum computing
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
Graduate Attributes and Skills Not entered
Course organiserDr Raul Garcia-Patron Sanchez
Tel: (0131 6)50 2692
Course secretaryMiss Yesica Marco Azorin
Tel: (0131 6)505113
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