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Physical Review Research
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- 1Reinforcement learning speeds up trapped-ion quantum computing▼Machine learning optimizes trapped-ion quantum computing – Reinforcement learning beats state-of-the-art techniques for
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.
- 2Systematic review examines AI in university physics teaching▼Artificial intelligence in university physics education: a systematic review of empirical studies
A systematic review of empirical studies on artificial intelligence in university physics education has been published, pulling together research on how AI tools are being used and what effects they have on teaching and learning at university level. The review consolidates existing findings rather than presenting new experiments, offering educators a broad picture of the state of AI in physics instruction.