Quantum Information Theory (QIT)

Course content

  • Review of Probability Theory and Classical Information Theory (Random Variables, Shannon Entropy, Coding)
  • Formalism of Quantum Information Theory (Quantum States, Density Matrices, Quantum Channels, Measurement)
  • Quantum versus Classical Correlations (Entanglement, Bell inequalities, Tsirelson's bound)
  • Basic Tools (Distance Measures, Fidelity, Quantum Entropy)
  • Basic Results (Quantum Teleportation, Quantum Error Correction, Schumacher Data Compression)
  • Quantum Resource Theory (Quantum Coding Theory, Entanglement Theory, Application: Quantum Cryptography)

MSc Programme in Mathematics
MSc Programme in Physics
MSc Programme in Mathematics with a minor subject
MSc Programme in Quantum Information Science

Learning outcome
  • Knowledge: The student will have become familiar with the mathematical formalism of quantum information theory and will have learned about the most fundamental results of the subject.
  • Skills: The student will be able to apply the learned knowledge in new situations and will be able to apply the abstract results in concrete examples.
  • Competences: The student will have a sound all-round understanding of the subject

4 lectures and 2 tutorials each week for 7 weeks.

Bachelor in Mathematics, Physics or Computer Science

Academic qualifications equivalent to a BSc degree is recommended.

7,5 ECTS
Type of assessment
Oral examination, 20 min
Type of assessment details
20 minutes per person with 20 minutes preparation time.
Exam registration requirements

6 mandatory homework assignments, each of which must be passed.

Written aids allowed

Written aids allowed during preparation and examination.

Marking scale
7-point grading scale
Censorship form
No external censorship
Several internal examiners.

Same as ordinary exam. If the compulsary homework assignments have not been passed, the student must (re)submit the non-passed assignments. The assignments must be approved three weeks before the beginning of the re-exam week.

Criteria for exam assessment

The student should convincingly and accurately demonstrate the knowledge, skills and competences described under Intended learning outcome.

Single subject courses (day)

  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 163
  • Exercises
  • 14
  • Exam
  • 1
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 2
No limit
The number of seats may be reduced in the late registration period
Study Board of Mathematics and Computer Science
Contracting department
  • Department of Mathematical Sciences
Contracting faculty
  • Faculty of Science
Course Coordinators
  • Matthias Christandl   (10-666b756c76776471676f437064776b316e7831676e)
  • Freek Gerrit Witteveen   (2-697a437064776b316e7831676e)
Saved on the 25-08-2023

Are you BA- or KA-student?

Are you bachelor- or kandidat-student, then find the course in the course catalog for students:

Courseinformation of students