发表机构
Tongji University; Institute of Modern Physics, Chinese Academy of Sciences（同济大学; 中国科学院近代物理研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
FUSION是一款基于技能的核物理代码研究智能体，可解决通用智能体生成错误物理约定输入的问题，覆盖20种核物理代码，含6万余页文献，采用MIT许可。
AI 中文摘要
运行陌生的核物理代码通常并非因物理本身的难度而困难，而是需要完成一系列任务：找到并构建该程序、学习其输入约定，以及判断看似合理的输出是否真的正确。通用编码智能体可协助完成前两项任务，但可能让最后一项任务更难——它可能生成遵循错误物理约定的输入文件。FUSION通过针对特定代码的技能解决这一问题。一项技能会从公共源代码获取代码，从经验证的输入出发，运行并解析计算过程，记录已知的故障模式，且必须在达到规定容差的前提下复现指定基准，才可报告结果。当前版本覆盖20种代码，涵盖光学模型与反应、核结构、裂变与统计模型、天体物理与R矩阵分析，以及重离子输运领域。它还包含来自nucl-th文献的61167页可离线搜索的合集，用户笔记与凭证则存放在公共仓库之外。FUSION采用MIT许可协议，可在此获取，文档在此。本文将阐述其设计、当前版本背后的检查机制，以及从输入到与实测数据对比的完整计算示例。
英文摘要
Running an unfamiliar nuclear-physics code is rarely difficult because of the physics alone. One must find and build the program, learn its input conventions, and decide whether a plausible output is actually correct. A general-purpose coding agent helps with the first two tasks but may make the last one harder: it can write an input file that runs with the wrong physical convention. FUSION addresses this problem with code-specific skills. A skill obtains the code from its public source, starts from a verified input, runs and parses the calculation, records known failure modes, and must reproduce a stated benchmark to a stated tolerance before reporting a result. The current release covers twenty codes, spanning optical models and reactions, nuclear structure, fission and statistical models, astrophysics and R-matrix analysis, and heavy-ion transport. It also includes an offline, searchable collection of 61 167 pages derived from the nucl-th literature. User notes and credentials remain outside the public repository. FUSION is available under the MIT license at https://github.com/jinleiphys/FUSION; documentation is at https://vibeinscience.com. Here I describe the design, the checks behind the current release, and one complete calculation from input to comparison with measured data.
Comments11 pages, 10 figures. Platform at https://github.com/jinleiphys/FUSION (MIT), documentation at https://vibeinscience.com
