Closing the reality gap in quantum devices

Rods of artificial light

Image by Christopher Burns on Unsplash

"... our study has demonstrated the utility of using physics-aware machine learning to narrow the reality gap".

David Craig

In the paper 'Bridging the Reality Gap in Quantum Devices with Physics-Aware Machine Learning', published in Physical Review X, David Craig together with colleagues from this department, Engineering, Statistics and the University of Basel, explains how they were able to infer the disorder potential of a nanoscale electronic device from electron-transport data using physics-aware machine learning.

The resulting model found internal disorder profiles, and was also able to accurately predict voltage settings required for specific device operating regimes.

Read more about this exciting new work on the University's News channel: 'New Study uses machine learning to bridge the reality gap in quantum devices', and click on the link above to download the full paper from Physical Review X.