{
  "abstract": "We present FM-JADES-v1, a self-supervised foundation model for James Webb Space Telescope ({\\em JWST}) deep-field science, trained with 482,444 objects from the {\\em JWST} Advanced Deep Extragalactic Survey (JADES) Data Release 5 using multi-band imaging and the photometric catalog. The shared embedding space is trained without class labels. We demonstrate that FM-JADES-v1 can serve as a powerful tool for object discovery and improving property measurements using two experiments, blind active discovery and few-band photometric redshift. For blind object discovery, FM-JADES-v1 identifies rare object populations such as high-redshift galaxies and Little Red Dots (LRDs) without any prior population labels or population-specific selection criteria. These rare populations emerge as isolated islands in the embedding space, which can be identified without prior astrophysical knowledge. For few-band photometric redshift, FM-JADES-v1's learned embeddings achieve $σ_{\\rm NMAD}=0.157$ in a strictly controlled three-band (F115W/F200W/F356W) photo-$z$ benchmark, compared to $σ_{\\rm NMAD}= 0.44$ for template fitting. These results demonstrate the potential of self-supervised multi-modal representations as scalable discovery spaces for large astronomical surveys. Applied to ongoing and future wide-field surveys from JWST, Roman, Euclid, and Rubin/LSST, this framework could enable systematic searches for rare populations, as well as enabling multiple downstream tasks such as improving astrophysical property measurements.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.11879",
  "author_total": 5,
  "authors": [
    {
      "name": "Jiani Ding"
    },
    {
      "name": "Minghao Yue"
    },
    {
      "name": "Yongda Zhu"
    },
    {
      "name": "Xiaohui Fan"
    },
    {
      "name": "Yufeng Luo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/1twvzn3ja5rjx.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.11879",
  "fulltext_url": null,
  "id": "1twvzn3ja5rjx",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.11879",
  "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",
      "astro-ph.GA"
    ],
    [
      "openalex",
      "3103|Galaxies: Formation, Evolution, Phenomena"
    ]
  ],
  "openalex": "W7212268201",
  "pdf_url": "https://arxiv.org/pdf/2609.11879",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-10",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/1twvzn3ja5rjx.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:26Z",
      "native_id": "2609.11879",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.11879"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.GA",
      "subfield": "galaxies"
    }
  ],
  "title": "Learning JWST. I. A Foundation Model for New Population Discoveries and Morphology-Aware Photometric Redshift Measurements in the JADES Survey",
  "title_text": "Learning JWST. I. A Foundation Model for New Population Discoveries and Morphology-Aware Photometric Redshift Measurements in the JADES Survey",
  "type": "preprint",
  "updated_at": "2026-10-30T12:20:26Z",
  "url": "https://research.draconitic.com/paper/1twvzn3ja5rjx",
  "venue": "arXiv",
  "versions": []
}