Reinforcement learning optimizes ion shuttling on trapped-ion quantum chips and reduces operations by up to 36.3% versus heuristics across multiple architectures.
Schmale, Hybrid quantum-classical computation – from infrastructure to algorithms, Institutionelles Repositorium der Leibniz Universit¨ at Hannover 10.15488/20338 (2026)
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Reinforcement learning for ion shuttling on trapped-ion quantum computers
Reinforcement learning optimizes ion shuttling on trapped-ion quantum chips and reduces operations by up to 36.3% versus heuristics across multiple architectures.