Mmastodon ScienceScience first seen 4 h ago, last 3 min ago, peak #2
Reinforcement learning speeds up trapped-ion quantum computing
Original: Machine learning optimizes trapped-ion quantum computing – Reinforcement learning beats state-of-the-art techniques for
Researchers at the Max Planck Institute for the Science of Light and the Albert Einstein Institute have shown that reinforcement learning can outperform state-of-the-art techniques for shuttling ions in trapped-ion quantum computers. The machine learning approach optimizes how ions are moved within the processor, a key bottleneck for scaling the technology. The results were published in Physical Review Research.
Why now: A new study demonstrates a machine learning method beating established techniques in a leading quantum computing platform, drawing attention from the research community.
Max Planck Institute for the Science of LightAlbert Einstein Institutetrapped-ion quantum computingreinforcement learning
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Evidence
- Machine learning optimizes trapped-ion quantum computing – Reinforcement learning beats state-of-the-art techniques for ion shuttling ➡️ https://www. aei.mpg.de/1515479/machine-lea rning-optimizes-trapped-ion-quantum-computing 📄 https:// journals.aps.org/prresearch/ab… · mpi_grav@academiccloud.social · 6
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