Mmastodon ScienceScience first seen 10 h ago, last 1 h ago, peak #2

Reinforcement learning improves 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 Gravitational Physics report that reinforcement learning outperforms state-of-the-art techniques for shuttling ions in trapped-ion quantum computers. Machine learning was used to optimize the transport of ions, a key operation for scaling up this leading quantum computing platform. The results were published in Physical Review Research, with physicists highlighting the promise of AI methods for controlling quantum hardware.

Why now: The demonstration that machine learning can beat established control methods in quantum computing is a notable advance that physicists are sharing.

Max Planck Institute for Gravitational PhysicsPhysical Review Researchtrapped-ion quantum computingreinforcement learning

Open on mastodon →

Rank over time, top of the chart is #1. 2 snapshots from 1 h ago to 1 h ago.

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 · 10

API: https://socialmediatrends-api.osmike.com/v1/trends/456916