{
  "abstract": "Quantum error correction (QEC) relies on repeated parity extraction, mid-circuit measurement (MCM), reset, feed-forward, and scheduling, yet these primitives are usually assessed either in isolation or through resource-demanding experiments. We introduce a few-sample benchmark of QEC-relevant primitives based on an MCM implementation of the quantum approximate optimization algorithm (QAOA) with a fixed set of linear parameters (LR-QAOA). For a chosen code, the QAOA Hamiltonian is constructed from its check structure, such that the resulting circuit mimics the syndrome-extraction connectivity and MCM pattern while producing a direct algorithmic signal, the approximation-ratio r. The LR-QAOA depth, defined by the number of QAOA layers, plays a role analogous to the number of repeated syndrome-extraction rounds in a QEC experiment. From QPU executions, the decay of r with depth defines an effective hardware error, which we map to an equivalent two-qubit depolarizing rate λeff. We compare direct and MCM-mediated implementations across 10 QPUs from IBM, IQM, and Quantinuum, with circuits containing up to 2950 MCM operations. On Quantinuum's Helios-1 and H2-1, we run code-structured LR-QAOA benchmarks for surface-code, triangular color-code, and bivariate-bicycle qLDPC Hamiltonians up to 81, 91, and 48 data qubits, respectively, using up to 480 MCM operations. On IBM ibm_phoenix, we implement the surface-code structure and compare the LR-QAOA response with logical-memory experiments, observing a correlation between the benchmark and the logical performance across different regions of the QPU. Its construction and low resource requirements provide a practical benchmark for comparing hardware generations and QEC implementations before full logical-memory experiments are performed.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2610.05928",
  "author_total": 2,
  "authors": [
    {
      "name": "J. A. Montanez-Barrera"
    },
    {
      "name": "Kristel Michielsen"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/cwfxmdsc3a0v5.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2610.05928",
  "fulltext_url": null,
  "id": "cwfxmdsc3a0v5",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2610.05928",
  "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",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7220699551",
  "pdf_url": "https://arxiv.org/pdf/2610.05928",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-05",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/cwfxmdsc3a0v5.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:30:52Z",
      "native_id": "2610.05928",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2610.05928"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Evaluating the performance of QEC primitives on quantum processors at large width and depth",
  "title_text": "Evaluating the performance of QEC primitives on quantum processors at large width and depth",
  "type": "preprint",
  "updated_at": "2026-10-30T12:33:41Z",
  "url": "https://research.draconitic.com/paper/cwfxmdsc3a0v5",
  "venue": "arXiv",
  "versions": []
}