{
  "abstract": "Fast radio bursts (FRBs) are millisecond-duration extragalactic pulses whose discovery requires searches over large signal-parameter spaces and the rejection of candidate sets dominated by radio-frequency interference and noise. Integrating quantum processors into FRB searches requires a workflow connecting telescop data to hardware-compatible models. Here we develop a pipeline that converts raw search-mode PSRFITS data into dynamic-spectrum segments and identifies FRB-like signals using a hybrid Quantum Vision Transformer (QViT). On labelled FAST data, the selected QViT achieves a mean accuracy of 94.00% and recall of 98.30%, with similar performance to a compact classical Vision Transformer. Recall reaches 97.11% on an FRB source excluded from training and model selection. Real-device execution on 82 segments yields a mean simulator-hardware Hellinger fidelity of 0.9161 +/- 0.0074. The workflow connects raw telescope data to quantum-assisted identification and provides an experimental basis for assessing the measurement requirements that must be addressed before survey-scale deployment.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.15108",
  "author_total": 13,
  "authors": [
    {
      "name": "Li He"
    },
    {
      "name": "Xuan Yang"
    },
    {
      "name": "Feng Xiong"
    },
    {
      "name": "Songbo Zhang"
    },
    {
      "name": "Qiuhao Chen"
    },
    {
      "name": "Yuchen He"
    },
    {
      "name": "Yunxiang Yang"
    },
    {
      "name": "Jun Lu"
    },
    {
      "name": "Claudio Furtado"
    },
    {
      "name": "Amilcar R. Queiroz"
    },
    {
      "name": "Xinping Deng"
    },
    {
      "name": "Yang Wu"
    },
    {
      "name": "Xuefeng Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/d51ajdpqarjjg.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.15108",
  "fulltext_url": null,
  "id": "d51ajdpqarjjg",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.15108",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "astro-ph.HE"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "3103|Radio Astronomy Observations and Technology"
    ]
  ],
  "openalex": "W7213357352",
  "pdf_url": "https://arxiv.org/pdf/2609.15108",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/d51ajdpqarjjg.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:21:25Z",
      "native_id": "2609.15108",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.15108"
    }
  ],
  "subjects": [
    {
      "field": "astronomy",
      "origin": "arxiv:astro-ph.HE",
      "subfield": "high-energy-astrophysics"
    },
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Hardware-aware quantum attention for fast radio burst identification",
  "title_text": "Hardware-aware quantum attention for fast radio burst identification",
  "type": "preprint",
  "updated_at": "2026-10-30T12:21:25Z",
  "url": "https://research.draconitic.com/paper/d51ajdpqarjjg",
  "venue": "arXiv",
  "versions": []
}