arXiv cs.AI· Eunbi Rha, Abhijatmedhi Chotrattanapituk, Mouyang Cheng, Chung-tao Chou, Shenyong Ye, Ashley S. Dale, Long Ju, Luqiao Liu, Mingda Li·· 3 小时前AI 评分53
QUANTA：面向自主量子材料表征的智能体 AI 框架
Autonomous Quantum Measurement with Agentic AI
AI 导读
研究团队提出 QUANTA，一个用于自主量子材料表征的智能体 AI 框架。该框架以 PPMS 为实验平台，结合科学文献、实验协议与历史测量的检索增强，以及实验规划、故障排除和数据解读的专用智能体，并由确定性控制层验证仪器操作；在拓扑 Weyl 半金属 TaP 的输运测量和磁性材料 Co2MnGa 的非线性响应研究中演示了能力。
正文 · 原文
Abstract:Quantum materials exhibit diverse electronic and functional phenomena, but their characterization requires extensive experimental expertise, iterative decision-making and accumulated laboratory knowledge that is difficult to document and transfer. Here we introduce Quantum Agent (QUANTA), an agentic artificial intelligence (AI) framework for autonomous quantum-materials characterization. Using a widely adopted Physical Property Measurement System (PPMS) as an experimental platform, QUANTA combines retrieval augmentation using scientific literature, experimental protocols and prior measurements with specialized agents for experimental planning, troubleshooting, and data interpretation. A separate deterministic control layer validates instrument actions. Guided by incoming data, QUANTA evaluates measurement quality, revises experimental plans and selects subsequent measurements. We demonstrate these capabilities through transport measurements of the topological Weyl semimetal TaP, as well as investigations of nonlinear responses in magnetic material Co2MnGa. These results establish QUANTA as a generalizable framework for evidence-driven, safeguarded and closed-loop quantum-materials characterization.
| Subjects: | Materials Science (cond-mat.mtrl-sci); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.38850 [cond-mat.mtrl-sci] |
| (or arXiv:2610.38850v1 [cond-mat.mtrl-sci] for this version) | |
| https://doi.org/10.48550/arXiv.2610.38850 arXiv-issued DOI via DataCite |
Submission history
From: Eunbi Rha [view email]
[v1]
Wed, 28 Oct 2026 20:33:06 UTC (11,028 KB)
来源：arXiv cs.AI · arxiv.org