Mmastodon ScienceScience first seen 1 d ago, last 7 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 of Gravitational Physics report that reinforcement learning outperforms state-of-the-art techniques for shuttling ions in trapped-ion quantum computers. The machine-learning approach optimizes how ions are moved within the hardware, a key bottleneck for scaling these systems. The findings are published in Physical Review Research.
Why now: A new result showing AI beating established methods in quantum computing hardware control is notable to the physics and quantum-tech community.
Max Planck Institute of Gravitational PhysicsPhysical Review Researchtrapped-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 · 11
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