{
  "abstract": "Context. Galaxy clusters sometimes host synchrotron radiation on scales of approximately 100 kpc to approximately 1 Mpc, with a surface brightness only a few times the image noise. This diffuse cluster radio emission is a sensitive probe of magnetic fields and intracluster medium dynamics, but disentangling the underlying physical processes requires statistically large samples spanning a wide range of cluster masses, dynamical states, and redshifts, together with a sufficient sensitivity to low-surface-brightness emission. Aims. We explore two techniques for improving the detection of diffuse emission in galaxy cluster images, relative to a baseline classifier: the scattering transform (ST) and squeeze-excitation (SE) attention. Methods. We integrated an ST encoder into a dual-branch classifier (DualSSN) and a scattering network (ScatterNet). We incorporated SE attention into the DualSSN and dual-branch convolutional neural network (DualCSN). These classifiers were then benchmarked against a simple convolutional neural network (CNN), across ten image pre-processing configurations and three cropping strategies. Performance was evaluated on small labelled datasets from the second data release of the LOFAR Two-metre Sky Survey overlapping with the Second Planck catalogue of Sunyaev-Zel'dovich sources (LoTSS-DR2/PSZ2). Results. Alongside the multi-branch approach with SE and ST, cropping the image to a fixed number of telescope beams and uv tapering (smoothing to a coarser angular resolution) improve classification performance, while tacking multiple pre-processed versions of an image does not. Conclusions. Scattering-transform-based multi-branch architectures with beam-normalised cropping are a promising direction for diffuse emission classification in the SKA era.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2607.28349",
  "author_total": 2,
  "authors": [
    {
      "name": "Markus Bredberg"
    },
    {
      "name": "Emma Tolley"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6xg16fmb32kxd.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2607.28349",
  "fulltext_url": null,
  "id": "6xg16fmb32kxd",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2607.28349",
  "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.CO"
    ],
    [
      "openalex",
      "3103|Radio Astronomy Observations and Technology"
    ]
  ],
  "openalex": "W7171979445",
  "pdf_url": "https://arxiv.org/pdf/2607.28349",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-31",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6xg16fmb32kxd.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:41Z",
      "native_id": "2607.28349",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2607.28349"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.CO",
      "subfield": "cosmology"
    }
  ],
  "title": "Multi-branch classification of diffuse cluster radio emission from the LOFAR two-metre sky survey",
  "title_text": "Multi-branch classification of diffuse cluster radio emission from the LOFAR two-metre sky survey",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:41Z",
  "url": "https://research.draconitic.com/paper/6xg16fmb32kxd",
  "venue": "arXiv",
  "versions": []
}