PROBING PARTICLE PHYSICS WITH ARTIFICIAL INTELLIGENCE

Abstract

Particle physics experiments have long research cycles and high barriers to entry. Limited human resources make it difficult to fully explore and analyze large volumes of collision data. Agents based on large language models can write code, retrieve literature, and carry out multi-step analyses, offering an opportunity to address this challenge. This article focuses on the Just Furnish Context (JFC) agent framework and examines results produced by the framework, including the CMS H→τ+τ- signal-strength measurement and the ALEPH Lund jet-plane density measurement, as well as their implications for particle physics research. It also summarizes the framework's current limitations and discusses prospects for benchmark-dataset construction, data processing at next-generation large-scale scientific facilities, and the training of future physicists.