Insider Brief
Google researchers demonstrated an AI system that continuously learns from quantum error-correction data to keep a quantum computer calibrated while it is running, reducing interruptions and improving reliability.
The reinforcement learning approach reduced logical error rates by about 20% beyond conventional calibration and made performance 3.5 times more stable under artificially introduced hardware drift on Google’s Willow quantum processor.
The researchers say the technique could help future fault-tolerant quantum computers operate autonomously for much longer periods by continuously adapting to changing hardware conditions.
A Google-led research team has demonstrated a quantum computer that continuously learns from its own errors while it is running, replacing one of the biggest operational bottlenecks in quantum computing with an artificial intelligence system that adapts as conditions change.
