AI and the World's Hard Problems · Quantum physics & quantum computing · arXiv · 2026-10-20
Large Language Model Steering of Acousto-Optic Tweezer Arrays
The authors used a general-purpose large language model as a human-in-the-loop strategy layer for a neutral-atom tweezer platform. When separable feedback stalled, the LLM guided a switch from multiplicative row-column correction to a drift-corrected local response-matrix method. For a 10×10 acousto-optic deflector array, the Gaussian-peak coefficient of variation fell from 20.30% to 1.57% in 30 candidate-update rounds, with an experimentalist authorizing each waveform.