Day 2 Dec-3 2021
Session 3 10:45-11:30

Developing technologies towards an error-corrected quantum computer

Yu Chen
Google Quantum AI Lab, USA

In this talk, I will give an overview on the technology developments in Google Quantum AI Lab. I will describe how these developments enabled us to build quantum systems with higher computational power for algorithms with higher complexities. A proof-of-principle example was given by the demonstration of beyond-classical computation (AKA quantum supremacy), where quantum computers can outperform classical counterparts on certain computational tasks. In the post-beyond-classical era, we are focusing on building technologies for an error-corrected quantum computer for fault-tolerant computations. I will describe a sequence of milestones we hope to achieve en route to such an error-corrected quantum machine, as well as the progress we have made towards achieving those milestones in Google Quantum AI Lab.

Yu Chen leads the Hardware Metrology Team in Google Quantum AI Lab. He and his team are responsible for developing metrology tools to improve our quantum computing system performance. He earned his PhD in physics from the University of Minnesota and did postdoctoral research at the University of California, Santa Barbara. Since joining Google in 2014, Yu and his team have been working to build fundamental understandings to the technology stack. These span from optimizing component performance such as gate or readout to developing next-generation hardware, such as cryogenic systems, necessary to scale Google’s quantum computing systems.