This research paper describes AlphaQubit, a machine learning decoder for quantum error correction, which is a critical component of building large-scale quantum computers. AlphaQubit uses a recurrent transformer network to learn how to decode the surface code, a type of quantum error-correction code. The decoder demonstrates superior performance compared to existing decoders on real and simulated data from Google's Sycamore quantum processor. The research highlights the potential of machine learning to advance quantum computing by going beyond human-designed algorithms and directly learning from experimental data.

https://www.nature.com/articles/s41586-024-08148-8