ACIT4321 Quantum Information Technology Emneplan

Engelsk emnenavn
Quantum Information Technology
Master's Degree Programme in Applied Computer and Information Technology
10 stp.


Quantum information technology implements quantum phenomena to process information and communicate it beyond the limits of the classical world. According to the EU Quantum Technologies Flagship report, such technology is based on the following pillars:

  • Quantum computation
  • Quantum communication
  • Quantum simulation
  • Quantum metrology and sensing

This course will introduce students to the first three of these fields, by equipping them with knowledge of principles, ideas, and methods. Many of these methods are also applicable within several other fields.

Prior knowledge in quantum physics is not required. The students will be trained to create their own quantum algorithms, simulate quantum systems, and implement the corresponding programs on classical and quantum computers. By implementing calculations and simulations of quantum systems, the students will learn about the fundamental quantum phenomena and key concepts. Moreover, in order to lay the proper foundation, the fundamental concepts of classical information theory is introduced.

A selection of recently published quantum algorithms and methods, including communication protocols, computational methods of modern quantum physics, and optimization algorithms, will be presented and analysed. Particular focus will be given to applications in data science in order to address research challenges in sustainable systems. Finally, the most recent challenges and particular proof of concept problems, including so-called quantum supremacy, will be addressed.

Anbefalte forkunnskaper

Knowledge of standard classical optimization algorithms would be beneficial. Familiarity with undergraduate physics is also an advantage, but by no means any prerequisite.


Students taking the course should be familiar with elementary calculus, including the concepts of complex numbers and numerical methods, and with basic linear algebra. Moreover, the students should be in command of a programming language/computing environment such as, e.g., Python, MATLAB or C(++).

In this regard, it is worth mentioning that the first lectures of the course will be spent on reminding the students of the basic concepts from mathematics.


A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence: 


On successful completion of the course the student

  • is able to model and simulate numerically simple quantum systems and processes - both on classical and quantum computers.
  • is familiar with fundamental key concepts within information theory such as Shannon Entropy, noiseless and noisy-channel coding theorems, and optimal coding algorithms.
  • knows what a qubit is and how the information content grows when qubits are connected.
  • is familiar with the elementary operations, or gates, of quantum computing - including gates such as the Hadamard gate and CNOT.
  • knows the present state of the art when it comes to existing quantum computers.
  • can implement simple quantum algorithms and run them on actual quantum computers.
  • knows basic quantum communication protocols such as key distributions and secret sharing and understands the ideas behind them.


On successful completion of the course the student

  • can independently devise, implement and run calculations and simulations of simple quantum systems.
  • will have the necessary knowledge to design her/his own quantum algorithms.
  • is familiar with several methods, such as Shor’s algorithm and quantum annealing, which enables quantum computers to solve problems considerably faster than classical computers.
  • is familiar with how quantum technology affects traditional encryption schemes, and provides novel ones.

General competence

On successful completion of the course the student

  • is familiar with several phenomena specific to quantum physics - such as quantization, particle interference, collapse of the wave function and entanglement.
  • is familiar with how information may be described by quantitative means - both within a classical and a quantum context.
  • knows how to revise and improve on implementations of quantum programs.
  • can address some of the practical challenges related to building quantum computers.
  • knows the importance of quantum computing within information technology and the open challenges yet to be solved in this scope. 


  • A brief re-acquaintance with vectors, matrices and complex numbers
  • Computational methods of quantum physics
  • Introduction to quantum phenomena
  • Introduction to classical information theory
  • Qubits and quantum gates
  • Entanglement and interference as key components of quantum computing
  • Fundamental quantum algorithms
  • Quantum annealing as a way of addressing optimization problems
  • Quantum cryptography
  • The challenge of de-coherence and openness in quantum systems

Arbeids- og undervisningsformer

The teaching is organized in sessions where the subject material is presented, and in sessions where the students solve problems on their laptops and prototype quantum computers. The latter is done  using online cloud platforms currently provided by enterprises such as, e.g., IBM and D-Wave. Between these sessions, the students are expected to work independently, using their computers, access to quantum computers, and course notes.

In the last stage of the cource, the students are required to complete and present an individual project that involves (i) simulation of a quantum system/process, (ii) simulation of a quantum communications protocol, or (iii) creation of a quantum code and its implementation on a quantum processor using an online cloud platform. The project should be concluded by submitting a report which provides a description of the project, its motivation and implementation, and an analysis the obtained results.

Arbeidskrav og obligatoriske aktiviteter


Vurdering og eksamen

The exam consists of two parts:

1. An individual project report of about 2000 - 4000 words. The report counts 50% towards the final grade.

2. A 30 minute individual oral exam, which includes a 10 minute presentation of the candidates project. The oral exam counts 50% towards the final grade. Both exams must be passed in order to pass the course. The oral exam cannot be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for applying for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

In the event of a postponed examination in this course the exam may be held as an oral exam. Oral exams cannot be appealed.

Hjelpemidler ved eksamen

The student can bring their own project report. The student is also allowed to make use of her/his own computer for the presentation of the project.


For the assessment, a grading scale from A to E is used. A denotes the highest and E the lowest passing grade, and F denotes a fail.


Two internal invigilators/examiners. External examiner is used periodically.


Professor Sølve Selstø


The course overlaps 3 ECTS with ACIT4320.