![]() ![]() 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. Reading List The principal source will be lectures slides provided during the course. Critically read and understand scientific literature on quantum computing.Master notions of more advanced topics, such as error correction on algorithms for near-term architectures.Discuss the difference of performance between classical and quantum computer for different computational tasks.Explain and analyse quantum algorithms described in quantum circuit and measurement-based quantum computing models.Use the mathematical framework of quantum computation to predict outcomes of quantum circuits.On completion of this course, the student will be able to: Programme Level Learning and Teaching Hours 2,ĭirected Learning and Independent Learning Hours Learning and Teaching activities (Further Info) This course is open to full year Visiting Students only, as the course is delivered in Semester 1 and examined at the end of Semester 2.Īcademic year 2022/23, Available to all students (SV1) If in doubt, consult the course lecturer. Visiting students are required to have comparable background to that assumed by the course prerequisites listed in the Degree Regulations & Programmes of Study. Information for Visiting Students Pre-requisites Other requirements: Quantum Mechanics (PHYS09053) OR Principles of Quantum Mechanics (PHYS10094)) OR ( Introduction to Linear Algebra (MATH08057) AND Probability with Applications (MATH08067)) OR Informatics Research Review (INFR11136) OR Research Methods in Security, Privacy, and Trust (INFR11188) Postgraduate or visiting students must have taken similar courses providing this background in their undergraduate degrees. Undergraduate students must have passed either Quantum Mechanics or both Introduction to Linear Algebra and Probability with Applications. For external students where this course is not listed in your DPT, please seek special permission from the course organiser.īasic knowledge of linear algebra, vector spaces, probability theory, complex numbers, models of computation, computability and intractability. ![]() This course is open to all Informatics students including those on joint degrees. Advanced Topics: quantum error correction, algorithm for near-term architectures, unconditionally secure quantum cloud computingĮntry Requirements (not applicable to Visiting Students) Pre-requisites Quantum Computing via measurement-based model: Description of graph state and measurement calculus Quantum Algorithms such as Grover's Search, Deutsch-Jozsa, Bernstein-Vazirani or Shor. Quantum subroutines such as Phase Kick-back, Quantum Fourier Transform or Phase-Estimation The first quantum protocols: Quantum teleportation and super dense coding Quantum Computing via quantum circuit model: Description of qubit and universal set of gates. ![]() Axioms of Quantum Mechanics, describing quantum system, quantum operators, composition, entanglement and measurements Basic concepts from Linear Algebra necessary for understanding the axioms of Quantum Mechanics, We finish the course by surveying few more advanced topics, such as quantum error correction, algorithms for near-term architectures and secure delegated QC. ![]() We cover the most important quantum subroutines and their application to well-known quantum algorithms and compare their performance with respect to classical computing. The two models of quantum circuit and measurement-based quantum computing will be introduced. The course will start with a brief introduction of the mathematical framework of QC. The aim of this course is to give students a basic overview of the rapidly growing field of Quantum Computation (QC). Postgraduate Course: Introduction to Quantum Computing (INFR11099) Course Outline School DRPS : Course Catalogue : School of Informatics : Informatics ![]()
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