Course Exam
260061 VO Tensor network methods in many-body physics (2023S)
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WHEN?
Location: Oskar-Morgenstern-Platz 1, Room 05.128, or as agreed upon (see below).Important: Beyond the exam dates indicated in u:find, there is also the possibility to make individual appointments for exams. It is recommended that students interested in taking the exam contact Prof. Schuch (norbert.schuch@univie.ac.at) prior to registering for the exam to discuss the date and time of the exam.
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).
- Registration is open from Mo 04.09.2023 08:00 to Mo 25.09.2023 12:00
- Deregistration possible until We 27.09.2023 12:00
Examiners
Information
Examination topics
The exam will cover the entire material taught in the course, as published on the course website. Alternatively, the material covered in the reading list can be examined.
Assessment and permitted materials
The exam will be conducted as an oral exam of 30 minutes. The exam will cover the material taught in the first part of the course, together with the material taught either in specialization Track A or Track B. Students who wish to take both tracks will be examined on both tracks (exam time 40 minutes), and additionally earn ECTS points for course 250148 "Mathematical Aspects of Tensor Networks in Many-Body Physics".Important: Beyond the exam dates indicated in u:find, there is also the possibility to make individual appointments for exams. It is recommended that students interested in taking the exam contact Prof. Schuch (norbert.schuch@univie.ac.at) prior to registering for the exam to discuss the date and time of the exam.
Minimum requirements and assessment criteria
Students must demonstrate knowledge of the topics covered in the first part of the lecture, as well as in the chosen specialization Track A or Track B. The exam will both includes questions testing the knowledge of the material, and its application to concrete examples, such as the properties of specific tensor network models.
Last modified: Tu 30.01.2024 13:46