Online, in blocks
Mo., 18.10.2021, 15:45 PM
All course materials are available via the ILIAS course. Please, register for the course and exercise in C@mpus first. You should be added to the ILIAS course automatically. If there are any problems, write an email to Daniel Vietz.
Mixed states, density operators and their applications are understood. Central algorithms such as QPE and QFT are clear at the circuit level. State preparation and oracle substitution can be applied. Transpilation and the effect on depth of algorithms are recognized. The meaning of read errors is clear. Measurement of arbitrary observables over Pauli strings is explained algorithmically. HHL is conceptually understood. The structure of hybrid variational algorithms is clear, as is the influence of barren plateaus. The treatment of categorical data, dimension reduction, and the structure of neural networks is understood. The structure of exemplary quantum neural networks is clear. Clustering, classification, kernel methods and their possible realization using quantum computers is understood - and thus the potential of quantum machine learning is seen. Furthermore, selected topics of the lecture "Grundlagen der Quanteninformatik" are deepened.