{
  "abstract": "Parnassus is a fast detector-simulation and reconstruction framework that maps truth-level particles directly to reconstructed particles. In this work, we investigate cross-detector transfer learning by adapting a Parnassus model for the ALEPH detector to the SLD detector. ALEPH and SLD have similar detector responses, as they were both targeting hadronic $Z$-pole $e^+e^-$ events, while differing substantially in the underlying detector technology, reconstruction, and archived data representation. We initialize the SLD particle model with weights learned on ALEPH, fine-tune it on SLD, and compare it with the same architecture trained directly on SLD. The ALEPH-initialized model gives substantially improved particle- and jet-level agreement with the SLD reference, including a factor of 5.2 improvement in the charged-particle angular response and an improvement in the jet angular resolution from $1.73$ to $1.15$ times the SLD reference. The results show that detector-response information learned on ALEPH can be reused when modeling SLD and motivate reusable pretrained Parnassus models for legacy $e^+e^-$ detectors, which is especially critical for experiments without access to the original software pipeline. With this paper, we also release an AI-ready version of simulated SLD $e^+e^-$ events.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.25061",
  "author_total": 3,
  "authors": [
    {
      "name": "Ya-Feng Lo"
    },
    {
      "name": "Chi Lung Cheng"
    },
    {
      "name": "Benjamin Nachman"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dv7f1zsyz0hj2.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.25061",
  "fulltext_url": null,
  "id": "dv7f1zsyz0hj2",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.25061",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "hep-ex"
    ],
    [
      "arxiv",
      "hep-ph"
    ],
    [
      "arxiv",
      "physics.ins-det"
    ],
    [
      "openalex",
      "3106|Particle Detector Development and Performance"
    ]
  ],
  "openalex": "W7214109737",
  "pdf_url": "https://arxiv.org/pdf/2609.25061",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-13",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dv7f1zsyz0hj2.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:39Z",
      "native_id": "2609.25061",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.25061"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.ins-det",
      "subfield": "applied-instrumentation"
    },
    {
      "field": "physics",
      "origin": "arxiv:hep-ex",
      "subfield": "high-energy"
    }
  ],
  "title": "Cross-Detector Transfer Learning with Parnassus: From ALEPH to SLD",
  "title_text": "Cross-Detector Transfer Learning with Parnassus: From ALEPH to SLD",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:39Z",
  "url": "https://research.draconitic.com/paper/dv7f1zsyz0hj2",
  "venue": "arXiv",
  "versions": []
}