(May 7, 2024/Munich) The practical course will provide the ability to model optimization problems for quantum computers, as well as an introduction to practical work with existing quantum computers. Four computers are currently available in the QAR Lab for this purpose: IBM Q System Two, IonQ Aria-2, Fujitsu DAU, D-Wave Advantage.
In cooperation with our industry partners BMW Group, SAP and Siemens projects with high relevance for concrete applications are calculated by our students on quantum computers in this semester. With the three use cases (1) Topology Optimization (BMW), (2) VM Balance Assignment (SAP), (3) Image Classification (SAP), (4) BnB hybrid Optimization (Siemens) and (5) Distribution Modelling (Siemens), the students will explore the main applications of quantum computing: machine learning, simulation and optimization.
We are pleased to make this possible for the 7th time and are looking forward to the results at the end of this semester.
The Quantum Computing Optimization Challenge is a practical course initiated by Prof. Dr. Claudia Linnhoff-Popien, head of the Chair of Mobile and Distributed Systems at LMU Munich. It took place for the first time in 2020 and has been an integral part of the curriculum ever since. This practical course teaches the ability to model optimization problems for quantum computers, as well as an introduction to practical work with existing quantum computers. Four computers are currently available for this purpose in the QAR Lab: IBM Q System Two, IonQ Aria-2, Fujitsu DAU, D-Wave Advantage. In cooperation with well-known partners from industry, tasks with strong relevance for practical applications are assigned each semester. The students have the opportunity to execute and compare one task on two computers. In the summer semester 2024, it takes place for the 7th time. Use cases in areas of optimization, machine learning and simulation are on the agenda.