Universität Wien
Warning! The directory is not yet complete and will be amended until the beginning of the term.

260096 VU Quantum Information Theory -Quantum Computing & Machine Learning (2023W)

5.00 ECTS (3.00 SWS), SPL 26 - Physik
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 15 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Monday 02.10. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 09.10. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 16.10. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 23.10. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 30.10. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 06.11. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 13.11. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 20.11. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 27.11. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 04.12. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 11.12. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 08.01. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 15.01. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien
  • Monday 22.01. 09:00 - 11:30 Seminarraum, Zi.504-506, Währinger Straße 17, 5. Stk., 1090 Wien

Information

Aims, contents and method of the course

[This event is planned to be face-to-face and presence is mandatory.]

This event gives an introduction to quantum information theory with a focus on quantum computing and quantum machine learning mainly from the theoretical point of view but experimental possibilities will be also discussed. The course provides also Hand-On, e.g. a set of quantum gatter will be provided with which we can build basic quantum algorithms and test them. Realization on present and upcoming quantum computers will be discussed.

The course builds on the knowledge of a basic course on quantum mechanics and introduces to qubits, quantum gates, circuits, measurement problem, quantum algorithms, artificial neural networks, simple machine learning algorithms (e.g. PCA, k-means), error correction schemes and basics of decoherence. (Classical) machine learning knowledge is not needed, an introduction will be given before discussing the quantum versions.

Method: lectures, problem solving problems within the class, Hand-on, and problems for take-away.

Depending on the wish of the students it will be either in English or German.

Assessment and permitted materials

This event is an interactive one, therefore the final grade is an average of active and regular participation, short exams within the event (announced in due time) and home-works/reports. No absence without announcement beforehand (per email).

Minimum requirements and assessment criteria

basics in quantum mechanics; average between regular (mandatory) attendance*, activity (25%), short exams (25%) and home-works (50%).
*Nobody who is ill or feels ill should attend the course. These absences have to be annouced per email before the course and can be compensated by written works.

Examination topics

everything discussed in the lectures

Reading list

will be given in the lectures

Association in the course directory

M-VAF A 2, M-VAF B

Last modified: Mo 25.09.2023 14:08