{
  "abstract": "The currently under construction SKA telescopes will allow for observations at unprecedented sensitivities in their respective electro-magnetic frequency ranges, enabling both faster and deeper surveys. A cost to this is the enormous amounts of data generated, necessitating scalable data reduction pipelines. This paper focuses on the imaging pipeline, which transforms measured visibilities into images of the sky. It extends a previous imaging framework that decentralizes the imaging process by spatial frequency across two nodes, which we retroactively name SURFIT, to multiple nodes. Specifically, this paper generalizes the descriptions of the deconvolution algorithms to account for images received from multiple nodes, as opposed to just one. It also describes how to prepare the datasets so that proper load balancing is achieved, and provides a method to estimate the scalability of the framework to an even larger number of nodes. We term this overall framework SMURFIT. We evaluated our framework across two simulated datasets based on SKA telescope configurations, as well as a smaller real dataset from ALMA, and found that it demonstrated largely linear speedup in visibility processing for up to 10 nodes, while reconstructing images of roughly the same quality for all but one of our test cases. We also show how the new load balancing strategy can be used to model SMURFIT's theoretical scaling, which we demonstrate for up to 50 nodes for our simulated datasets.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "name": "Sunrise Wang"
    },
    {
      "name": "Simon Prunet"
    },
    {
      "name": "Shan Mignot"
    },
    {
      "name": "Andre Ferrari"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dcq7shrac6vgb.bib",
  "cited_by": 0,
  "doi": "10.2139/ssrn.6967740",
  "fulltext_url": null,
  "id": "dcq7shrac6vgb",
  "issns": [],
  "landing_url": "https://hal.science/hal-05842457v1",
  "language": "en",
  "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": [
    [
      "hal",
      "0.phys"
    ],
    [
      "openalex",
      "3103|Radio Astronomy Observations and Technology"
    ]
  ],
  "openalex": "W7165405924",
  "pdf_url": "https://hal.science/hal-05842457/document",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dcq7shrac6vgb.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:02Z",
      "native_id": "hal-05842457",
      "source": "hal",
      "url": "https://hal.science/hal-05842457v1"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "hal:0.phys",
      "subfield": "general"
    }
  ],
  "title": "SMURFIT: Spatial-frequency Multi-band Radio Fourier Imaging Technique",
  "title_text": "SMURFIT: Spatial-frequency Multi-band Radio Fourier Imaging Technique",
  "type": "preprint",
  "updated_at": "2026-10-30T12:18:02Z",
  "url": "https://research.draconitic.com/paper/dcq7shrac6vgb",
  "venue": "HAL",
  "versions": []
}