{
  "abstract": "When the parameter of a PDE surrogate is the flow domain itself, the key/value set of an attention model must encode that domain. We present CARS (Coronary Artery Rapid Surrogate), a learned surrogate for the finite-volume solution map of the steady incompressible Navier-Stokes equations on coronary lumens built from image-derived centerlines. CARS maps a centerline with per-point lumen radius and a scalar inlet flow rate to pressure and velocity at arbitrary query points. The attention focal set is the case's own centerline, so geometry fusion costs $O(N n_f)$ rather than $O(N^2)$ in the number of evaluation points. Trained per territory on $2{,}700$ OpenFOAM solutions with synthetic focal lesions, CARS reaches relative $\\ell_2$ errors of $0.120/0.149$ (pressure/velocity) on left-coronary and $0.063/0.119$ on right-coronary test sets, in $87$~ms per case against a solver wall-clock of $572$-$1{,}063$~s. It outperforms four parameter-matched neural operators, and accuracy saturates eightfold below the operating focal count. Fractional flow reserve derived from the predicted pressure matches the CFD label at Pearson $r = 0.941/0.993$ and reproduces the $\\mathrm{FFR}\\le 0.8$ decision in $97.7\\%/96.3\\%$ of held-out cases. The predicted velocity does not satisfy continuity closely enough for derived quantities, and the weights are territory-specific.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.30498",
  "author_total": 3,
  "authors": [
    {
      "name": "Reza Akbarian Bafghi"
    },
    {
      "name": "Sukirt Thakur"
    },
    {
      "name": "Maziar Raissi"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/02kmaavv1gm5q.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.30498",
  "fulltext_url": null,
  "id": "02kmaavv1gm5q",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.30498",
  "language": null,
  "licence": "CC-BY-NC-ND-4.0",
  "licence_label": "CC BY-NC-ND 4.0",
  "licence_source": "article",
  "licence_url": "http://creativecommons.org/licenses/by-nc-nd/4.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.CE"
    ],
    [
      "arxiv",
      "physics.flu-dyn"
    ]
  ],
  "openalex": null,
  "pdf_url": "https://arxiv.org/pdf/2610.30498",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/02kmaavv1gm5q.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:34:34Z",
      "native_id": "2610.30498",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.30498"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:physics.flu-dyn",
      "subfield": "fluid-dynamics"
    }
  ],
  "title": "CARS: a centerline-anchored attention surrogate for coronary blood flow on skeleton-generated lumen geometries",
  "title_text": "CARS: a centerline-anchored attention surrogate for coronary blood flow on skeleton-generated lumen geometries",
  "type": "preprint",
  "updated_at": "2026-10-30T12:34:34Z",
  "url": "https://research.draconitic.com/paper/02kmaavv1gm5q",
  "venue": "arXiv",
  "versions": []
}