管控高能物理的智能体工具链
Reining in an Agentic Harness for High Energy Physics
- University of Alabama（阿拉巴马大学）
- Fermi National Accelerator Laboratory（费米国家加速器实验室）
机构由 AI 辅助整理，请以论文原文为准。
中文总结 AI 辅助
针对智能体系统在高能物理领域能力跨模型复用难的问题，提出将稳定工作流升级为带版本科学操作、用通用协议暴露，结合任务定制工具与社区注册表，以科学契约解决操作不匹配，构建便携式HEP智能体工具链。
中文摘要 AI 辅助
智能体系统如今可处理理论、唯象学及实验高能物理（HEP）领域的任务，但其科学能力难以在不同大语言模型、提供商及工具链间复用。我们主张将这些工作流中稳定的部分升级为带版本的科学操作，并通过通用协议对外提供。现有通用工具链可通过特定任务的工具集与技能集针对HEP进行定制，而社区维护的注册表将使这些能力可被发现与引用。我们指出，独立开发的操作间在约定、假设及有效域上的不匹配是其组合的潜在障碍，并讨论了机器可读的科学契约作为一种可能的解决方案。这些设计原则与评估指南为构建便携式、社区维护的HEP智能体工具链提供了近期可行路径。
英文摘要
Agentic systems now address tasks across theoretical, phenomenological, and experimental high energy physics (HEP), but their scientific capabilities remain difficult to reuse across different large language models, providers, and harnesses. We argue that stable parts of these workflows should be promoted into versioned scientific operations and exposed through common protocols. Existing general-purpose harnesses can then be specialized for HEP through task-specific sets of tools and skills, while community-maintained registries would make these capabilities discoverable and citable. We identify mismatches in conventions, assumptions, and domains of validity among independently developed operations as a potential obstacle to their composition, and discuss machine-readable scientific contracts as one possible solution. These design principles and evaluation guidelines provide a near-term path toward a portable and community-maintained agentic harness for HEP.
