Introduction to Quantum Computing

Course content

This course will provide an introduction to the field of quantum computing and information, covering a variety of topics ranging from computation and cryptography to foundations of quantum physics. Once familiar with the fundamentals, we will explore current research topics and discuss how quantum phenomena give rise to new algorithms for machine learning, quantum computational supremacy, cryptographic schemes with unprecedented security guarantees, and device-independent protocols.

As part of the exercises, you will run simple quantum programs on an actual, albeit noisy, quantum computer available through the cloud.

Topics covered include

- Fundamentals of quantum computing (quantum states, superposition, measurement, unitaries)

- The circuit model (qubits, unitary gates)

- Basic protocols (e.g. teleportation, superdense coding, state discrimination)

- Basic quantum algorithms (e.g. Deutch-Josza, Grover, HHL) and the concept of quantum computational supremacy

- Bell inequalities, non-local games and the concept of device-independence

- Basic quantum protocols for cryptography, e.g. quantum key-distribution

- Noisy intermediate scale quantum devices and quantum error-correction



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

Learning outcome

Knowledge: the students will have an understanding of the basic principles of quantum information and computing, including knowledge of basic protocols, applications, and algorithms.

Skills: Carry-out computations corresponding to valid transformations of quantum states as a result of measurement or application of unitary gates.

Competencies: Ability to analyze simple quantum protocols and reason about basic information processing capabilities of quantum computers. 

4 hours of lectures and 2 hours of exercise classes per week for 7 weeks.

1) Linear algebra: LinAlg or LinAlgDat course or equivalent
2) Basic probability: SS or DMA or StatFys course or equivalent


Students will receive written individual feedback on their assignement solutions. Collective oral feedback will be given during lectures and exercise classes regarding the problems/questions posed to the class.

7,5 ECTS
Type of assessment
Continuous assessment
Oral examination, 25 minutes
Type of assessment details
The students' performance will be evaluated via
- 2 individual, equally weighted assignments during the term
- Final oral exam (with 25 minutes preparation), where the student presents one randomly selected topic from a previously known list of topics

The assignments will account for 40% and the oral exam for 60% of the final grade.
Only certain aids allowed

All aids allowed for the assignments.

Personally handwritten notes on paper allowed during the 25-minute preparation period before the examination.

Marking scale
7-point grading scale
Censorship form
External censorship

25 minutes oral exam without preparation or aids.

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
  • 134
  • Theory exercises
  • 14
  • Exam
  • 30
  • English
  • 206


Course number
7,5 ECTS
Programme level
Full Degree Master

1 block

Block 1
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
  • Albert H. Werner   (6-5b6976726976447165786c326f7932686f)
  • Laura Mancinska   (9-716572676d72776f65447165786c326f7932686f)
  • Morten Kjaergaard   (11-6f6d6c63677469636374664270646b306d7730666d)
Saved on the 28-02-2023

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