MM866: Introduction to HPC and Quantum Computing

Study Board of Science

Teaching language: English
EKA: N310076102
Assessment: Second examiner: None
Grading: Pass/Fail
Offered in: Odense
Offered in: Autumn
Level: Master

STADS ID (UVA): N310076101
ECTS value: 5

Date of Approval: 23-04-2024

Duration: 1 semester

Version: Approved - active


If there are fewer than 5 students the course might run as a guided reading course. 

Entry requirements


Academic preconditions

Students taking the course are expected to have knowledge of:
  • Programming (in at least one programming language) 
  • Basic concepts of linear algebra (vector spaces, matrices, eigenvalues)
  • Basic concepts of complex numbers and vector spaces
  • Basic understanding of logic gates 

Course introduction

The aim of the course is to use small HPC systems and quantum computers, which is important in regard to future computer architecture. The skills learned in this course can be applied in a variety of subjects, such as applied mathematics, physics, chemistry and biology. 

The course builds on the knowledge acquired in the courses MM553: Computational Physics, and MM533: Mathematical and Numerical Analysis, and gives an academic basis for studying the topics of quantum computing.

Expected learning outcome

The learning objective of the course is that the student demonstrates the ability to:
  • Understand the concept of parallel computing. 
  • Write code that uses multiple cores on multiple computers simultaneously.
  • Understand the principle of how quantum computers operate. 
  • Develop small quantum circuits.
  • Present the results in a short presentation


The following main topics are contained in the course:

  • High Performance Computing 
  • Quantum Computing


See itslearning for syllabus lists and additional literature references.

Examination regulations

Exam element a)








Second examiner: None




Full name and SDU username


Normally, the same as teaching language

Examination aids

To be announced during the course

ECTS value


Indicative number of lessons

56 hours per semester

Teaching Method

At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
  • Intro phase: 24 hours
  • Training phase: 32 hours, hereof tutorials: 3 hours
Activities during the study phase:

  • Solving the project assignments
  • Reflection upon the intro and training sections.
  • Self-study of specific topics from the textbook
  • Independent review of the intro phase and training phase

Teacher responsible

Name E-mail Department
Benjamin Jäger Computational Science


Administrative Unit

Institut for Matematik og Datalogi (matematik)

Team at Educational Law & Registration


Offered in


Recommended course of study

Profile Education Semester Offer period

Transition rules

Transitional arrangements describe how a course replaces another course when changes are made to the course of study. 
If a transitional arrangement has been made for a course, it will be stated in the list. 
See transitional arrangements for all courses at the Faculty of Science.