Towards a quantum computer that learns from its errors

Google Research published a reinforcement learning-based quantum error correction control framework in Nature, letting an agent continuously tune thousands of control parameters using error detection events to counter drift during computation. In experiments injecting artificial drift on the Willow superconducting processor, RL control improved logical stability by 3.5x and further reduced the logical error rate by 20% on top of expert calibration.