trapped-ion quantum computing

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Reinforcement learning speeds up trapped-ion quantum computing▼Machine learning optimizes trapped-ion quantum computing – Reinforcement learning beats state-of-the-art techniques forMmastodon Science1053 min ago
Researchers at the Max Planck Institute for Gravitational Physics report that a reinforcement learning algorithm outperforms state-of-the-art methods for shuttling ions in trapped-ion quantum computers. The machine learning approach optimizes how ions are moved and arranged, a key bottleneck for scaling up quantum hardware. The results were published in Physical Review Research, and physicists are sharing the work as an example of AI improving quantum control.