Presentation
Quantum computers have an exponentially large state space, which has motivated many proposals for using them in machine learning. In this talk, Viktor will give an introduction to quantum machine learning: the main ideas, what has been achieved, and where the main difficulties lie. He will then discuss quantum reservoir computing, where a fixed quantum system is combined with a simple trained readout, and present some of their results on what makes a good quantum reservoir.
Speaker
Viktor Svensson is a DSTrain postdoc at the Department of Physics, University of Oslo. He works on the theory of quantum dot systems and superconductor–semiconductor hybrids. His research interests include Majorana bound states for topological quantum computing and quantum reservoir computing. Within reservoir computing, he is particularly interested in how the physical properties of quantum dot networks affect their performance as reservoirs for machine learning.
Program
11:30 – Doors open and lunch is served
12:00 – "Quantum machine learning and reservoir computing" by Viktor Svensson (Postdoctoral Fellow, Department of Physics)
This event is open for all students, PhD candidates, postdocs, and everyone else who is interested in the topic. No registration needed.
About the seminar series
Once a month, dScience will invite you to join us for lunch and professional talks at the Science Library. In addition to these, we will serve lunch in our lounge in Kristine Bonnevies house every Thursday. Due to limited space (40 people), this will be first come, first served. See how to find us here.
Our lounge can also be booked by PhDs and Postdocs on a regular basis, whether it is for a meeting or just to hang out – we have fresh coffee all day long!