We are glad to present
Richard Küng
Johannes Kepler University Linz
Monday, 04 Nocember 2024
at Lise Meitner Lecture Hall at Universität Wien
Boltzmanngasse 5, 1090 Vienna, 1st floor
Scalable quantum-classical interfaces and their applications to learning in the quantum realm
Large-scale quantum (computing) experiments do not work in isolation. Substantial classical computing power is required to control the architecture and process its results. This necessarily creates information-transmission bottlenecks at the interface between quantum and classical realms.
In this colloquium, I will present quantum-classical interfaces that address these information-transmission bottlenecks. Dubbed classical shadows (of quantum systems), these leverage frame theory and high-dimensional probability theory to obtain a succinct classical description of the underlying quantum system. These can then be used to efficiently predict many features of the quantum system in a streaming fashion. Building on these ideas, we also establish mathematically rigorous synergies between quantum experiments (to obtain data) and machine learning (to learn how to make predictions).
Host: Borivoje Dakić
(Universität Wien)
For further information and a Zoom link please visit: https://vcq.quantum.at/colloquium-ss-24/
Program
17:00 Get together
17:30 VCQ Student talk by Martin Mauser: Data re-uploading: From experiment to generalisability of quantum machine learning
17:45 VCQ Colloquium Talk
