{
  "abstract": "Very-long-baseline interferometry (VLBI) may enable direct imaging of fine, event-horizon-scale black hole structures such as the photon ring. In particular, the n = 1 photon subring encodes information about black hole spin in its radial profile and azimuthal brightness modulation, making it a key proxy for spacetime properties. However, the n = 1 subring overlaps with emission from the n = 0 subring in observations, requiring isolation of the n = 1 subring for measurements. We present a convolutional neural network (CNN) capable of extracting the n = 1 subring from composite images containing n = 0 and n = 1 subrings. We simulate 111,000 m -ring images with eht-imaging to train and validate the CNN. The CNN accurately recovers the radial and angular brightness profiles of the n = 1 subring with a mean normalized cross correlation (NXcorr) of ∼0.99. The CNN provides a detection capability by predicting no false positives when input images lack an n = 1 subring. We perform feature extraction with ringfit to show that the CNN-predicted n = 1 subring accurately recovers the ground truth radial profiles and azimuthal brightness modulation, demonstrating the CNN’s capability to extract spin-sensitive features. We further test the CNN on black hole images generated by KerrBAM and general relativistic magnetohydrodynamic (GRMHD) simulations, finding that it recovers the overall n = 1 subring radial profiles while exhibiting discrepancies in the recovered intensity profiles. These results demonstrate the potential of deep learning methods to isolate the n = 1 subring from overlapping emission, providing a framework for analyzing future high-resolution black hole images from proposed VLBI missions such as the Black Hole Explorer (BHEX).",
  "abstract_shown": true,
  "affiliations": [
    "University of California",
    "Miller Institute for Basic Research in Science"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Courtney Duong",
      "orcid": "0009-0002-2194-4898"
    },
    {
      "affs": [
        0
      ],
      "name": "Frank Myhre",
      "orcid": "0009-0008-8192-928X"
    },
    {
      "affs": [
        1,
        0
      ],
      "name": "Joseph R. Farah",
      "orcid": "0000-0003-4914-5625"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/db70jvehp6r8m.bib",
  "cited_by": 0,
  "doi": "10.3847/1538-4357/aeab91",
  "fulltext_url": null,
  "id": "db70jvehp6r8m",
  "issns": [
    "1538-4357",
    "0004-637X"
  ],
  "landing_url": "https://iopscience.iop.org/article/10.3847/1538-4357/aeab91",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "feed-journal",
      "astronomy/general"
    ],
    [
      "openalex",
      "3103|Astrophysical Phenomena and Observations"
    ]
  ],
  "openalex": "W7223908795",
  "pdf_url": "https://iopscience.iop.org/article/10.3847/1538-4357/aeab91/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-27",
  "publisher": "American Astronomical Society",
  "ris": "https://research.draconitic.com/paper/db70jvehp6r8m.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:17Z",
      "native_id": "10.3847/1538-4357/aeab91",
      "source": "feed-iop",
      "url": "https://iopscience.iop.org/article/10.3847/1538-4357/aeab91"
    },
    {
      "first_seen": "2026-10-30T12:18:11Z",
      "native_id": "10.3847/1538-4357/aeab91",
      "source": "crossref",
      "url": "https://iopscience.iop.org/article/10.3847/1538-4357/aeab91"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "journal-openalex:3103|Stellar, planetary, and galactic studies",
      "subfield": "stellar"
    }
  ],
  "title": "Convolutional Neural Network for Extraction of n = 1 Photon Ring of Black Holes",
  "title_text": "Convolutional Neural Network for Extraction of n = 1 Photon Ring of Black Holes",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:11Z",
  "url": "https://research.draconitic.com/paper/db70jvehp6r8m",
  "venue": "The Astrophysical Journal",
  "versions": []
}