Agentic AI for Scientific Reasoning in Autonomous Quantum Sensing Experiments
We implement an agentic AI workflow built around a large language model (LLM) agent for autonomous experiments with nitrogen-vacancy (NV) centers in diamond. NV centers are a widely used platform for quantum sensing, and the ability to control many measurements from a computer makes NV experiments a natural setting for autonomous workflows. We make two main contributions. First, we demonstrate an autonomous NV experiment workflow that combines persistent project records, quantitative calculation and data analysis tools, and deterministic experiment control. In one autonomous experiment, the agent selected a single NV center, calibrated its resonant frequency, measured \(T_2^\ast\) with Ra...
| Authors | Takuya Isogawa, Ryotaro Okabe, Nutdech Phadetsuwannukun et al. |
|---|---|
| Primary category | quant-ph |
| Published | 27 July 2026 |
| Last updated at source | 27 July 2026 |
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