{
  "abstract": "We report forward random-circuit sampling (RCS) on the 120-qubit Nighthawk r2 superconducting processor (ibm_phoenix) with square-lattice connectivity, using 61 qubits, native CZ gates, and the standard cloud execution stack with no benchmark-specific calibration. Two independent fidelity estimators---mirror benchmarking and three- and four-patch cross-entropy benchmarking (XEB)---agree with each other at every measured depth, the mirror from 4 to 40 cycles and the patched estimators from 20 to 40 cycles, across more than two orders of magnitude of fidelity decay, and exceed the first-generation Nighthawk r1 device by more than an order of magnitude at fixed depth. The 36-cycle circuits sit at the depth where tensor-network contraction cost saturates at system size: a contraction-cost estimator validated against the published Sycamore and Zuchongzhi networks places the single-amplitude cost at $\\sim$$10^{22}$ complex operations. At $F_{\\mathrm{XEB}}(36)=2.3\\times10^{-3}$ under favorable memory assumptions this implies $1.2\\times10^{27}$ machine operations within the bounded-fidelity rejection-sampling model --- more than a century of runtime on the Frontier supercomputer --- to collect a $10^{6}$-sample ensemble, which takes only 19\\,s on Nighthawk r2. To our knowledge, this is the first demonstration of quantum advantage for a vanilla random-circuit sampling on a commercially and broadly accessible quantum processor that most non-expert quantum computer users can easily replicate.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.28657",
  "author_total": 6,
  "authors": [
    {
      "name": "Tigran Sedrakyan"
    },
    {
      "name": "Yuxuan Zhang"
    },
    {
      "name": "Hovnatan Karapetyan"
    },
    {
      "name": "Joshua D. Baktay"
    },
    {
      "name": "Hrant Gharibyan"
    },
    {
      "name": "Hayk Tepanyan"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/eg0bg3qx9qesq.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.28657",
  "fulltext_url": null,
  "id": "eg0bg3qx9qesq",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.28657",
  "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",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7214391943",
  "pdf_url": "https://arxiv.org/pdf/2609.28657",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/eg0bg3qx9qesq.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:29:50Z",
      "native_id": "2609.28657",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.28657"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computers",
  "title_text": "Quantum computational advantage in random-circuit sampling on IBM superconducting quantum computers",
  "type": "preprint",
  "updated_at": "2026-10-30T12:29:50Z",
  "url": "https://research.draconitic.com/paper/eg0bg3qx9qesq",
  "venue": "arXiv",
  "versions": []
}