Experimental Deep Reinforcement Learning for Error-Robust Gate-Set Design on a Superconducting Quantum Computer
Yuval Baum, Mirko Amico, Sean Howell, Michael Hush, Maggie Liuzzi, Pranav Mundada, Thomas Merkh, Andre R. R. Carvalho, Michael J. Biercuk · PRX Quantum · 2021
A bottleneck for scaling quantum hardware is solved: An AI-based technique to design quantum gates without knowledge of the physical model or the noise processes is demonstrated experimentally, outperforming the best human-designed gates.