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arXiv cs.AI· Zachary W. Gomez, Nathan Bittner, Jordan T. McCourt, Qingrui Cao, Sandesh S. Kalantre, Benjamin H. Alexander, Zhiren Zheng, Kenji Watanabe, Takashi Taniguchi, Aaron Sharpe·· 14 小时前AI 评分48

HERA:评估用于量子器件测量的自主智能体

HERA: Assessing an Autonomous Agent for Quantum Device Measurement

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研究团队提出自主智能体 HERA,用于执行量子器件的低温输运测量,其结论在两台多层石墨烯器件的堆叠顺序判断上与专家密封结论一致。知识库消融与数百次离线回放显示,接入实验室知识库后各模型设计的测量方案更优、推理更严谨。HERA 还在数小时专家工作开发新协议后,自主完成另一材料体系的超导性发现与表征。

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Abstract:Large language model agents have begun to carry out laboratory measurements, but their scientific conclusions are useful only if they hold up under scrutiny. Demonstrating this requires controlled studies because models are stochastic and the context a model is given steers its conclusions. Here we introduce HERA, an autonomous agent designed to carry out cryogenic transport measurements of quantum devices. HERA draws on a knowledge base curated by lab members that holds measurement protocols, software tools, and literature references. We assessed HERA with a blinded trial against an expert on the stacking order of two multilayer graphene devices, an ablation of its knowledge base, and hundreds of offline replays in which models designed the trial's central measurement without running it. HERA's conclusions matched the expert's sealed conclusions on both tested devices. The ablation and the replay studies measured the impact of the knowledge base across different models, showing that with it every model designed better measurements and reasoned more soundly. To test how readily HERA extends to a new problem, we tasked it with finding and characterizing superconductivity in a different material system. This required a few hours of expert time to develop a new experimental protocol, after which HERA did both autonomously. These results show that, with a knowledge base designed for the task, language model agents are capable of sound experimental science.
Comments: 16 pages, 5 figures, plus Supplementary Information (7 figures, 6 tables); data and code at this https URL and this https URL
Subjects: Mesoscale and Nanoscale Physics (cond-mat.mes-hall); Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.39074 [cond-mat.mes-hall]
  (or arXiv:2610.39074v1 [cond-mat.mes-hall] for this version)
  https://doi.org/10.48550/arXiv.2610.39074

arXiv-issued DOI via DataCite

Submission history

From: Zachary Gomez [view email]
[v1] Thu, 29 Oct 2026 00:08:00 UTC (14,856 KB)

来源:arXiv cs.AI · arxiv.org