Machine-learning-assisted correction of correlated qubit errors in a topological code
A fault-tolerant quantum computation requires an efficient means to detect and correct errors that accumulate in encoded quantum information.In the context of machine learning, neural networks are a promising new approach to quantum error correction.Here we show that a recurrent neural network can be trained, using only experimentally accessible da