Google Research Stabilizes "Willow" Quantum Processor Using Continuous Reinforcement Learning Control Layers - Quantum Computing Report

Google Quantum AI has introduced a hardware-control framework that unifies real-time calibration with active quantum error correction (QEC), allowing an autonomous reinforcement learning (RL) agent to stabilize logical qubits during uninterrupted execution. Published in Nature (“Reinforcement learning control of quantum error correction“), the engineering milestone addresses the primary bottleneck facing fault-tolerant quantum computing (FTQCs): environmental drift and material non-stationarity, which degrade microscopic device calibration and typically force operators to take systems offline for disruptive maintenance. By repurposing structural binary error-detection signals as a continuous, in-context training input, Google’s control system enables its next-generation Willow superconducting processor to continuously learn from its [...]

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