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Quantum Information Theory (QIT)
Provider: Faculty of Science

Activity no.: 5547-23-07-31 
Enrollment deadline: 06/02/2023
PlaceDepartment of Mathematical Sciences
Universitetsparken 5, 2100 København Ø
Date and time06.02.2023, at: 08:00 - 14.04.2023, at: 16:00
Regular seats50
ECTS credits7.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserMatthias Christandl    E-mail address: christandl@math.ku.dk
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 3
Scheme groupB
Exam formOral examination
Exam details20 minutes per person without preparation time.
Exam aidsWritten aids allowed during preparation and examination
Grading scale7 point grading scale. For PhD students: Passed / Not Passed
Criteria for exam assessmentThe student must in a satisfactory way demonstrate that he/she has mastered the learning outcome of the course
Censorship formSeveral internal examiners
Exam re-examinationSame as ordinary exam. If the compulsary home work assignments have not been passed, the student must hand in the non-passed assignments at least two weeks before the beginning of the re-exam week. If they pass the student can go to the re-exam
Course workload
Course workload categoryHours
Lectures28.00
Exercise(s)14.00
Preparation163.00
Exam1.00

Sum206.00


Content
- Review of Probability Theory and Classical Information Theory (Random Variables, Shannon Entropy, Coding)
- Formalism of Quantum Information Theory (Quantum States, Density Matrices, Quantum Channels, Measurement)
- Quantum versus Classical Correlations (Entanglement, Bell inequalities, Tsirelson's bound)
- Basic Tools (Distance Measures, Fidelity, Quantum Entropy)
- Basic Results (Quantum Teleportation, Quantum Error Correction, Schumacher Data Compression)
- Quantum Resource Theory (Quantum Coding Theory, Entanglement Theory, Application: Quantum Cryptography)

Learning outcome
- Knowledge: The student will have become familiar with the mathematical formalism of quantum information theory and will have learned about the most fundamental results of the subject.
- Skills: The student will be able to apply the learned knowledge in new situations and will be able to apply the abstract results in concrete examples.
- Competences: The student will have a sound all-round understanding of the subject

Teaching and learning methods
4 lectures and 2 tutorials each week for 7 weeks.

Remarks
The course is relevant for mathematics, physics students, and computer science students.

Academic qualifications:
Optional: basic courses in quantum mechanics, probability theory, information theory, advanced linear algebra

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