ACIT4321 Quantum Information Technology Emneplan

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 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.

One internal examiner.

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

• 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
• 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.

Skills 

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.can independently devise, implement and run calculations and simulations of simple quantum systems.
• can design her/his own quantum algorithms.

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, particle spin, entanglement and decoherence - and how they may manifest themselves within quantum computing.
• 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. 

10 ECTs overlap with the course PSYK1310 (15 ECTs).

Admission to the programme.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and competence:

Knowledge

The student has

• broad knowledge of key topics in the field of psychology

Skills

The student is capable of

• describing and discussing key topics in the psychology discipline

Competence

The student is capable of

• presenting subject matter to and sharing opinions with fellow students

Work and teaching methods used in the course are lectures, self-study and student-initiated group work. Seminars will also be held that focus on the presentation of psychology literature. Participation in these seminars is compulsory. Four one-hour tests will be held during the course.

• Participation at the seminars (80%)
• Three written texts (max. 900 words)

The required coursework must be approved before the students can take the supervised written exam.

Portfolio exam comprising four tests and a supervised written exam lasting four hours. All four tests must be passed before the student can take the supervised written exam. All the components must be awarded a pass grade before the exam as a whole can be passed. If the student fails one test, the student can retake this test. Resits/rescheduled attempts of the four tests can be taken once before the ordinary supervised written exam. Before the resit/rescheduled supervised written exam, students will be given a third and final attempt at one or more of the tests.

None

A–F. A grade will be awarded on the basis of the tests taken during the course (60%) and the result of the final written exam (40%). The student has a right to appeal the overall exam grade for the whole portfolio.

The course overlaps 3 ECTS with ACIT4320.