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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 Science1148 min ago
Researchers at the Max Planck Institute of Quantum Optics / Albert Einstein Institute report that reinforcement learning outperforms state-of-the-art control techniques for shuttling ions in trapped-ion quantum computers. The machine-learning approach optimizes ion transport, a key bottleneck for scaling trapped-ion hardware, and the results are published in Physical Review Research.