|
|
Main menu for Browse IS/STAG
Course info
OPT / KTI
:
Course description
Department/Unit / Abbreviation
|
OPT
/
KTI
|
Academic Year
|
2024/2025
|
Academic Year
|
2024/2025
|
Title
|
Quantum Information Theory
|
Form of course completion
|
Exam
|
Form of course completion
|
Exam
|
Long Title
|
Quantum Theory of Information
|
Accredited / Credits
|
Yes,
4
Cred.
|
Type of completion
|
Combined
|
Type of completion
|
Combined
|
Time requirements
|
Lecture
2
[Hours/Week]
Tutorial
1
[Hours/Week]
|
Course credit prior to examination
|
Yes
|
Course credit prior to examination
|
Yes
|
Automatic acceptance of credit before examination
|
No
|
Included in study average
|
YES
|
Language of instruction
|
Czech, English
|
Occ/max
|
|
|
|
Automatic acceptance of credit before examination
|
No
|
Summer semester
|
0 / -
|
0 / -
|
0 / -
|
Included in study average
|
YES
|
Winter semester
|
0 / -
|
0 / -
|
0 / -
|
Repeated registration
|
NO
|
Repeated registration
|
NO
|
Timetable
|
Yes
|
Semester taught
|
Winter + Summer
|
Semester taught
|
Winter + Summer
|
Minimum (B + C) students
|
not determined
|
Optional course |
Yes
|
Optional course
|
Yes
|
Language of instruction
|
Czech, English
|
Internship duration
|
0
|
No. of hours of on-premise lessons |
|
Evaluation scale |
A|B|C|D|E|F |
Periodicity |
každý rok
|
Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
|
Fundamental theoretical course |
Yes
|
Fundamental course |
Yes
|
Fundamental theoretical course |
Yes
|
Evaluation scale |
A|B|C|D|E|F |
Evaluation scale for credit before examination |
S|N |
Substituted course
|
None
|
Preclusive courses
|
N/A
|
Prerequisite courses
|
N/A
|
Informally recommended courses
|
N/A
|
Courses depending on this Course
|
N/A
|
Histogram of students' grades over the years:
Graphic PNG
,
XLS
|
Course objectives:
|
Introductory course in quantum information theory, quantum computing, and quantum communication. Students will get basic knowledge of this discipline and will be able to independently solve selected types of problems in this area.
|
Requirements on student
|
Course credit prior to examination is awarded for ative participation at the exercises and for successful solving of several homework sets. Oral exam covering the the taught subject matter as specified in the Content section.
|
Content
|
1. Physical aspects of information processing, quantum theory
2. Quantum states, quantum operations, quantum measurements, quantum entanglement
3. Quantum computer, quantum logic gates
4. Quantum Fourier transform, Shor's algorithm, quantum search algorithms
5. Physical implementations of quantum computers
6. Entropy in quantum information theory, quantum data compression
7. Quantum communication, quantum channels, quantum error correction
8. Quantum cryptography: principles and security proofs
9. Quantum cryptography: implementations
10. Quantum teleportation, entanglement swapping
11. Quantum communication networks, quantum repeaters
|
Activities
|
|
Fields of study
|
|
Guarantors and lecturers
|
|
Literature
|
-
Basic:
Bruß, Dagmar, Leuchs, Gerd. Lectures on quantum information. Weinheim, 2007. ISBN 9783527405275.
-
Basic:
Nielsen M. A., Chuang, I. L. Quantum Computation and Quantum Information. Cambridge University Press, 2004. ISBN 0521635039.
-
Recommended:
Beth, Thomas Leuchs, Gerd. Quantum information processing. Weinheim, 2005. ISBN 3527405410.
-
Recommended:
Peres, A. Quantum Theory: Concepts and Methods. Kluwer, Dordrecht, 1995.
-
On-line library catalogues
|
Time requirements
|
All forms of study
|
Activities
|
Time requirements for activity [h]
|
Homework for Teaching
|
50
|
Attendace
|
39
|
Preparation for the Exam
|
30
|
Total
|
119
|
|
Prerequisites - other information about course preconditions |
Knowledge of mathematical analysis, algebra, and quantum physics at the level of bachelor study of physics.
|
Competences acquired |
Knowledge of basic principles of quantum information theory, knowledge of basic quantum communication protocols, understanding of the working principles of quantum computers and quantum algorithms, ability to apply the acquired knowledge in problem solving. |
Teaching methods |
- Lecture
- Dialogic Lecture (Discussion, Dialog, Brainstorming)
|
Assessment methods |
|
|
|
|