{
  "abstract": "Bayesian QU-fitting is among the most accurate approaches for line-of-sight Faraday inference, but its per-pixel computational cost has made survey-scale application infeasible. QU-fitting is an alternative to Faraday synthesis with comparable accuracy in recovering line-of-sight Faraday components, but it has historically been computationally prohibitive at survey scale. Fitting to the Stokes spectra in $Q$ and $U$ through Bayesian inference is effective but slow. We introduce \\texttt{VROOM-SBI}, which uses simulation-based inference, particularly neural posterior estimation, to speed up inference. Our results are comparable to both Faraday synthesis and QU-fitting, and deliver a speedup of $\\sim$$500$ over classical QU-fitting implementations. We provide an open code repository and tools along with trained models via HuggingFace for the four standard depolarization models in common use, trained on VLA L-band frequency coverage.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2605.27538",
  "author_total": 2,
  "authors": [
    {
      "name": "Arpan Pal"
    },
    {
      "name": "Preshanth Jagannathan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/008hte589hacv.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2605.27538",
  "fulltext_url": null,
  "id": "008hte589hacv",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2605.27538",
  "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"
    ],
    [
      "arxiv",
      "astro-ph.GA"
    ],
    [
      "arxiv",
      "astro-ph.IM"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2605.27538",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/008hte589hacv.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:14Z",
      "native_id": "2605.27538",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2605.27538"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.CO",
      "subfield": "cosmology"
    },
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.GA",
      "subfield": "galaxies"
    },
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.IM",
      "subfield": "instrumentation-methods"
    }
  ],
  "title": "VROOM-SBI: A Fast Simulation-Based Bayesian Inference Methodology for Stokes QU-Fitting in Radio Interferometry",
  "title_text": "VROOM-SBI: A Fast Simulation-Based Bayesian Inference Methodology for Stokes QU-Fitting in Radio Interferometry",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:14Z",
  "url": "https://research.draconitic.com/paper/008hte589hacv",
  "venue": "arXiv",
  "versions": []
}