After successful completion of the course, students are able to understand mixed states, density operators and their applications. 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 possibility of realization using quantum computers is understood - and thus the potential of quantum machine learning is seen. Furthermore, selected topics of the "Fundamentals of Quantum Informatics" are deepened.

• Mixed states, density operators, reduced density operators
• Quantum Information
• QFT, QPE, Amplitude Amplification
• State Preparation & Oracle Replacement
• Transpilation, Connectivity, Readout Errors
• Hamilton Simulation, HHL Algorithm, Quantum Linear Algebra
• Pauli strings, measurement of arbitrary observables
• Variational Algorithms, VQE, QAOA, Warm-Starting, Barren Plateaus, Quantum Gradients
• Categorical data, dimension reduction, quantum neural networks, quantum no-free lunch
• support vector machines, quantum kernels
• Hybrid algorithms, quantum software engineering

Using what learned with QisKit und IBM Q.

Excercises:
1.3., 14 - 15 Uhr: WebEx
17.3, 22.3., 28.3., 10 - 13 Uhr: on site

Inverted Classromm - Watch videos by 10.3.2023, discussion afterwards at 17.3., 22.3., 28.3., on site from 13:00h.

During the exercises, the contents of the lecture will be practiced and consolidated by means of practical examples.

Kickoff:  22. Februar 2023, 11:00 Uhr, auf WebEx - Link:
https://unistuttgart.webex.com/unistuttgart/j.php?MTID=m20663b757f0ef8ef6efd4db7f977e0dd 

Materialien: 
Videos der Vorlesung, die Handouts sowie die Übungsblätter werden Online zu Verfügung gestellt.
Die Übungen selber als auch eine Frage- bzw. Diskussionsveranstaltung wird persönlich stattfinden. 

Barzen & Leymann (Vorlesung), Mandl (Übungen)

ECTS Breakdown :
6 ECTS entsprechen 150 Stunden

20 Stunden Vorlesung, 40 Stunden Vorlesungsvorbereitung, 15 Stunden Wiederholung für die Prüfung und
75 Stunden Übung

Kontakt:
Prof. Frank Leymann (Univ. Stuttgart) - frank.leymann@iaas.uni-stuttgart.de
Dr. Johanna Barzen   (Univ. Stuttgart) - johanna.barzen@iaas.uni-stuttgart.de
Dipl.-Ing. Alexander Mandl (Univ. Stuttgart) -  alexander.mandl@iaas.uni-stuttgart.de

Exercises and oral exam about lecture.

Quanteninformatik 1 (VO)
https://tiss.tuwien.ac.at/course/courseDetails.xhtml?dswid=6187&dsrid=286&courseNr=194128&semester=2022W

Quanteninformatik 1 (UE)
https://tiss.tuwien.ac.at/course/courseDetails.xhtml?dswid=4628&dsrid=418&courseNr=194132&semester=2022W