Machine Learning for Quantum 2021 will take place March 1-5, 2021, with an aim to bring together quantum physicists and experts in computer science and machine learning.
The last few years have seen a fast increase in the complexity of quantum technologies. In this context, recent ground-breaking 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 conference is centred around three key questions, which will be discussed 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). The conference, however, is platform-agnostic, and targets all quantum technology implementations.
Interested individuals and parties can register to attend via this link.
A full program summary can be accessed via this link.