{
  "abstract": "The efficient operation of accelerator facilities increas- ingly relies on rapid access to heterogeneous operational knowledge, including logbooks, interlock reports, machine parameters, and historical archive data. At ELBE, we pro- posed a Retrieval-Augmented Generation (RAG) frame- work that integrates facility documentation and operational records into a unified AI-assisted support tool for operators. The system is expected to index electronic logbooks, ma- chine archive time-series data, and subsystem manuals using domain-adapted embeddings stored in a vector database. User queries will be expected to be processed through a large language model that retrieves the most relevant oper- ational context and generates structured, operator-oriented responses with traceable source references. This contribu- tion presents the system architecture, data integration strat- egy, and challenges toward real-time AI-assisted accelerator operation",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "Journal reference: presented at IPAC'26, Deauville, France, May 2026, paper WEP6008, unpublished",
  "arxiv": "2609.27579",
  "author_total": 1,
  "authors": [
    {
      "name": "Najmeh Mirian"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/a5tj8a5rp2va9.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.27579",
  "fulltext_url": null,
  "id": "a5tj8a5rp2va9",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.27579",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "physics.acc-ph"
    ],
    [
      "arxiv",
      "physics.app-ph"
    ],
    [
      "arxiv",
      "physics.data-an"
    ],
    [
      "openalex",
      "1702|Topic Modeling"
    ]
  ],
  "openalex": "W7214191681",
  "pdf_url": "https://arxiv.org/pdf/2609.27579",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-23",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/a5tj8a5rp2va9.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:56Z",
      "native_id": "2609.27579",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.27579"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.acc-ph",
      "subfield": "applied-instrumentation"
    },
    {
      "field": "physics",
      "origin": "arxiv:physics.data-an",
      "subfield": "computational"
    }
  ],
  "title": "Integration of Retrieval-Augmented Generation for Knowledge Access in the ELBE Accelerator Control System",
  "title_text": "Integration of Retrieval-Augmented Generation for Knowledge Access in the ELBE Accelerator Control System",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:56Z",
  "url": "https://research.draconitic.com/paper/a5tj8a5rp2va9",
  "venue": "arXiv",
  "versions": []
}