Agentic AI—Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data

We present an agentic measurement of the thrust distribution in \(e^+e^-\) collisions at \(\sqrt{s}=91.2\) 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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Publication Details

Journal
Highlights in High-Energy Physics
Published
2026-09-30
DOI
https://doi.org/10.53941/hihep.2026.100010
Primary Topic
High-Energy Particle Collisions Research
Type
article
Field-Weighted Citation Impact
0.00

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Agentic AI—Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data

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Agentic AI—Physicist Collaboration in Experimental Particle Physics: A Proof-of-Concept Measurement with LEP Open Data

Jingyu Zhang, Anthony Badea, Chris McGinn, Yu-Chen Chen, G. M. Innocenti, Hannah Bossi, Tzu-An Sheng, The Electron-Positron Alliance, Austin Baty, Luna Chen, Yen-Jie Lee, Marcello Maggi
article en

Abstract

We present an agentic measurement of the thrust distribution in \(e^+e^-\) collisions at \(\sqrt{s}=91.2\) 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.

Highlights in High-Energy PhysicsVol. 2(3)
Istituto Nazionale di Fisica Nucleare (IT), Vanderbilt University (US), University of Illinois Chicago (US), University of Chicago (US), Istituto Nazionale di Fisica Nucleare, Sezione di Bari (IT), Massachusetts Institute of Technology (US)
U.S. Department of Energy, Office of Science
Industry, innovation and infrastructure
Openalex Percentile: Top 82%
High-Energy Particle Collisions Research
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