ACIT4321 Quantum Information Technology Course description

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.

Two internal examiners. External examiner is used periodically.

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:

Knowledge

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.

Skills

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.

This course covers topics selected to reflect the breadth and multidisciplinary nature of biomedical engineering. Material for the course is put together in cooperation with researchers, medical professionals and representatives from the healthcare industry. One of the objectives is to expose students to a variety of emerging technologies playing an important role in the paradigm shift towards preventive, personalized and precision medicine. The course also has a practical project that lasts for a short period where the students are assigned to any of the laboratories at OsloMet, medical/health care companies, or a department at local hospitals in the Oslo and Akershus region. The course is completed by the student giving an oral presentation of the practical project results.

No formal requirements over and above the admission requirements.

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.

Lectures and practical semester exercises. The students work both individually and in groups. The groups normally comprise 3-4;students. The student will supplement the lectures and lab with their own reading.;

Individual assigments

Practical training;

Practical semester exercise.

The following coursework is compulsory and must be approved before the student can attend;the exam:

• Semester exercise in a group of 3-4 students. A report between 7500 - 15000;words. The total working load will be approx. 60 hours per student.;

Individual written exam, 3 hours.

The exam grade can be appealed.

;

New/postponed exam

In case the number of students in the course is less than five, the exam will be automatically turned into an oral 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.

The final grade will be based on:

1) An individual/group (2-5 students) project report on a chosen topic and practical assignment (7 500 - 15 000 words) (50% of the final grade)

2) An individual oral exam (50% of 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.

Topics covered in this course:;

• Introduction to sensors and;actuators;
• Electrochemical sensors and;actuators;
• Optical sensors and;actuators;
• Multivariate calibration using optical and electrical;spectra;
• Evaluation of sensors and actuators for medical and health care;applications;