Agentic AI—Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data
Anthony Badea, Marcello Maggi, Christopher McGinn, Austin Baty, Yi Chen, Hannah Bossi, Gian Michele Innocenti, Jingyu Zhang, Yu-Chen Chen, Tzu-An Sheng, Yen-Jie Lee, The Electron-Positron Alliance
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Source: Crossref
Published: Sep 30, 2026
DOI: 10.53941/hihep.2026.100010
Open original source ↗Source abstract
We present an agentic measurement of the thrust distribution in collisions at GeV using ALEPH archived data. This work was carried out through an AI agent–physicist collaboration, using interactive natural-language prompting of Anthropic Claude and OpenAI Codex. Under physicist guidance, the agents wrote and executed all analysis code and drafted the majority of the text included in this paper. A fully-corrected thrust spectrum is obtained via Iterative Bayesian Unfolding and Monte Carlo based corrections. The principal contribution of this work is the demonstration of the agentic analysis, with thrust serving as a benchmark observable for the method. Dedicated precision measurements of thrust are reported in the community elsewhere. This work represents a step toward a theory–experiment loop in which AI agents assist with experimental measurements and theoretical calculations, and synthesize insights by comparing the results, thereby accelerating the cycle that drives discovery in fundamental physics. Our work suggests that precision physics, leveraging the open LEP data and advanced theoretical landscape, provides an ideal testing ground for developing AI agent systems for scientific applications.
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