Dr. Sebastian Feld
Quantum Machine Learning at LMU's QAR-Lab
Sonderforschungsbereich 876 "Verfügbarkeit von Information durch Analyse unter Ressourcenbeschränkung"
Prof. Dr. Katharina Morik
Quantum Computing, which is based on principles of quantum mechanics and so-called qubits as information units, has become increasingly relevant since the publication of algorithms by Shor and Grover in the 1990s. However, the scientific community has long been concerned with the possibility of a quantum computer, since famous physicist Richard Feynman postulated in his 1982 paper "Simulating Physics with Computers" that in order to simulate a quantum system a quantum computer is required. There are several approaches for such quantum computer architectures, such as Quantum Gate Computing and Adiabatic Quantum Computing. In the meantime, company D-Wave Systems is the first company to have built quantum annealing hardware based on Adiabatic Quantum Computing.
The talk is divided into two parts. First, an understanding of quantum mechanical fundamentals of quantum computing is developed, quantum gate model and adiabatic quantum computing are explained, and finally formalizations and solution methods for (combinatorial) optimization problems are shown. Second, activities of LMU Munich's "Quantum Applications and Research Laboratory" (QAR Lab) are presented. A particular focus is on topics of quantum machine learning.