用AI助手让重离子对撞机25年科学知识可查可用
AI-Powered Assistant for Long-Term Access to RHIC Knowledge
- 基于大模型与检索增强生成，整合实验文档与代码
- 支持自然语言查询，提升1EB级数据的可发现性
- 适合科研人员长期复现和新研究者快速上手
美国布鲁克海文国家实验室的相对论重离子对撞机（RHIC）在运行25年后，其海量数据（约1艾字节）及蕴含的科学知识亟需保存。为此，RHIC数据与分析保存计划（DAPP）推出一个基于大语言模型的AI助手系统，通过检索增强生成与模型上下文协议，实现对实验文档、工作流与软件的自然语言访问，旨在支持可复现性、教育及未来发现。该系统已部署并完成多实验集成，具备可持续、可解释的长期人工智能访问架构。实践表明，现代AI/ML工具能显著提升科学遗产数据的可用性与可发现性。
原文摘要 · Abstract (English)
As the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory concludes 25 years of operation, preserving not only its vast data holdings ($\sim$1 ExaByte) but also the embedded scientific knowledge becomes a critical priority. The RHIC Data and Analysis Preservation Plan (DAPP) introduces an AI-powered assistant system that provides natural language access to documentation, workflows, and software, with the aim of supporting reproducibility, education, and future discovery. Built upon Large Language Models using Retrieval-Augmented Generation and the Model Context Protocol, this assistant indexes structured and unstructured content from RHIC experiments and enables domain-adapted interaction. We report on the deployment, computational performance, ongoing multi-experiment integration, and architectural features designed for a sustainable and explainable long-term AI access. Our experience illustrates how modern AI/ML tools can transform the usability and discoverability of scientific legacy data.
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