Pre-Conference Workshops

Monday 26 August 2019, 09:00 - 17:00

These workshops will consist of a morning part with introductory lectures followed by two tutorial sessions in the afternoon. The morning lectures are intended for partici­pants of both workshops. However, the afternoon parts will run in parallel so you can choose only one of the two events upon registration (limited number of participants).

WS 1: Machine Learning for Experimental Quantum Physics

This one-day workshop introduces the principles of neural-network-based machine-learning applications in condensed matter, quantum mesoscopic physics, and quantum optics. In two lectures, the theoretical background of supervised learning with deep neural networks will be discussed, including convolutional networks, various regularization schemes, and an overview on existing applications. In a tutorial session elementary examples are demonstrated step-by-step and the participants will learn how to set up a simple neural network calculation using the Keras environment in Tensor Flow. The topics are geared towards experimental data analysis. The goal of the workshop is to enable participants to use elementary machine-learning techniques in their research. No previous knowledge is required, except for elementary command of python in the hands-on programming session at the end of the workshop. To participate in the hands-on session, a laptop with internet connection is needed.

Contact: Titus Neupert
Further lecturers / tutors: Mark Fischer (Uni Zürich), Eliska Greplova (ETHZ), Kenny Choo (Uni Zürich), Frank Schind­ler (Uni Zürich)

WS 2: Programming a Quantum Computer with Examples in Quantum Machine Learning

In this workshop we first provide a general introduction followed by a hands-on experience on how to program quantum computers with Qiskit. We show how to implement quantum circuits in Python, how to simulate them using classical computers, and how to run them on real quantum hardware via the IBM Q Experience. Based on this fundament, a quantum machine learning algorithm for classification is introduced and it is shown how to train and test it for any given dataset. To participate in this workshop basic knowledge of how to program in Python is required and a laptop with an internet connection. Ideally, you have already installed Qiskit and Qiskit Aqua (pip install qiskit / pip install qiskit_aqua).

Contact: Stefan Woerner
Further lecturer / tutor: Christa Zoufal (IBM Research – Zurich)

References:
http://qiskit.org, http://learnqiskit.org/, https://nbviewer.jupyter.org/github/Qiskit/qiskit-tutorial/blob/master/index.ipynb

Registration for the workshops

The workshops can hold only a limited number of participants. You can only register for a workshop if you have already registered as conference participant. After this go to the workshop registration module and fill in the required data. The module will close after the maximum number of participants is reached. In case you have to cancel the workshop registration, we therefore ask you to inform us immediately so your place can be re-opened for other interested persons.