Machine Learning for Quantum 2021

The last few years have seen a fast increase in the complexity of quantum technologies. In this context, recent groundbreaking experimental work has started to highlight the potential of advanced signal processing, such as machine learning and real-time adaptive techniques to speeding up, scaling up, and opening up new quantum technologies.

The goal of this online conference, taking place March 1-5, 2021, has been to bring together quantum physicists with experts in computer science and machine learning, to tackle these challenges together. Please find the conference program here. An introductory presentation to the conference, with statistical information and practicalities can be downloaded here. While the conference is now over, you can still access videos for most of the talks here.

This online conference is centered around three questions, which we will address over five days of tutorials, talks and discussions:
Q1 – how can a quantum sensor optimally extract information about its environment?
Q2 – how can we achieve fully automatic calibration and operation of multi-qubit circuits?
Q3– how can machine learning improve the performance of quantum algorithms for quantum chemistry?


This event is organised as a satellite Photonics Online Meetup (POM). Our approach is, however, platform-agnostic, and we target all quantum technology implementations.

Our tutorial speakers: