NFYK13005U Quantum Information

Volume 2018/2019
Education

MSc Programme in Physics

Content

Quantum Information aims at exploiting quantum mechanics to perform certain tasks (computation, measurements, communication, etc.) more efficiently than it is allowed by classical physics. The course will give an introduction to quantum information as well as to some of the physical systems where implementation of quantum information processing is being attempted. Special attention will be on quantum optical systems (atoms, ions, and photons).
In the course we will be dealing with the fundamental and often paradoxical structure of quantum mechanics. By working with these subjects the participants will not only be brought up to date we a very active field of research, but will also gain a deeper understanding of quantum mechanics.

Learning Outcome

Skills
After the course the students should be able to explain how the various quantum information protocols work and why they are better than any classical protocol. Furthermore the students should be able to describe how to implement quantum information protocols in practice and discuss some of the problems, which arise when one tries to do so.

More specifically the students should be able to:

  • describe how the BB84 quantum cryptography protocol works and how it is implemented in practice.
  • define entanglement for pure states, and describe how to use it for super dense coding, cryptography, and teleportation.
  • explain how entanglement may be generated experimentally for photons, ions and atoms.
  • explain what a quantum computer is and describe how the Deutsch and Grover algorithms and quantum simulation work on a quantum computer.
  • discuss general requirements for practical implementation of quantum computation and describe how these requirements are fulfilled for an ion trap.
  • explain the teleportation protocol and how it may be implemented experimentally.
  • explain Bell's inequalities and their violation in quantum mechanics
  • discuss how decoherence and imperfections appear and influence experiments and know how to describe it in terms of the density matrix.
  • relate the various parts of the course together and apply the knowledge gained in the course in new situations.

 

Knowledge
After the course students should know the elementary concept from quantum information theory including qubits, pure and mixed states, Bloch sphere, entanglement, super dense coding, teleportation, quantum repeaters, Bell’s inequalities, entanglement purification, quantum error correction, and quantum computation algorithms (Deutsch, Grover, and quantum simulation). Furthermore they should know how one can implement quantum information processing in simple experimental systems such as photons and trapped ions.

Competences
The student will learn how the different logical structure of quantum mechanics, compared to classical mechanics, enables new possibilities for e.g. computation, measurements, and communication.  Thereby the course will provide a deeper understanding of the quantum mechanics learned in previous courses. It will also provide the students with a background for further studies within quantum optics or quantum information, e.g. in a M.Sc. project

Literature

Various notes and articles.

It will be assumed that you have heard about the quantization of the electromagnetic field, either in a quantum optics course or some other course. It is assumed that you have a good background in quantum mechanics, e.g., through following an advanced quantum mechanics course. Also it may be an advantage if you have followed a course on Optical Physics and Lasers and on Quantum Optics, but it is not strictly necessary.
Lectures and exercises
  • Category
  • Hours
  • Exam
  • 0,5
  • Lectures
  • 26
  • Preparation
  • 140,5
  • Theory exercises
  • 39
  • Total
  • 206,0
Credit
7,5 ECTS
Type of assessment
Oral examination, 30 min
Without preparation time
Marking scale
7-point grading scale
Censorship form
No external censorship
More internal examiners
Re-exam

as the ordinary exam.

Criteria for exam assesment

see learning outcome