Arbeid med IT-systemer
På grunn av arbeid med IT-systemer kan du oppleve ustabilitet i tilganger til OsloMet sine systemer og tjenester i perioden 24.-26. mars. Sjekk driftsmeldingene for oppdateringer.
På grunn av arbeid med IT-systemer kan du oppleve ustabilitet i tilganger til OsloMet sine systemer og tjenester i perioden 24.-26. mars. Sjekk driftsmeldingene for oppdateringer.
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:
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 first few weeks of the course is dedicated to an introduction to key concepts in quantum physics. These concepts are introduced in a practical manner - with emphasis on simulation and phenomenology rather than theory.
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.
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 some relevant mathematical and numerical concepts will be revised during the the first lectures.
A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:
Knowledge
On successful completion of the course the student
Skills
On successful completion of the course the student
General competence
On successful completion of the course the student
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.
None
The assessment will be based on a portfolio of the following:
The portfolio will be assessed as a whole and 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.
All aids are permitted. For the oral exam, students will only have access to the project report.
Grade scale A-F.
Two internal examiners. External examiner is used periodically.
Sergiy Denisov
The course overlaps 3 ECTS with ACIT4320.