{
  "abstract": "Topological quantum memories need decoders that are both reliable and scalable, but these goals compete: globally informed decoders are accurate near threshold yet expensive, while strictly local rules are fast but can miss long-range structure. Motivated by recent recoverability and mixed-state viewpoints, we make this tradeoff operational for the dephased toric code through a decoder-level local recoverability diagnostic. We compare global MWPM corrections to quasi-local corrections inside a target region and define a matching ratio $R_{\\mathrm{match}}$, with mismatch $ε_{\\mathrm{match}}=1-R_{\\mathrm{match}}$. Across geometry families, $ε_{\\mathrm{match}}$ shows strong buffer-controlled suppression and is well organized by a two-geometry scaling form. For scaled families, especially $a=b=d/8$, $R_{\\mathrm{match}}$ exhibits a clear crossing and finite-size collapse near $p\\!\\sim\\!0.09$, consistent with a growing recoverability scale near the decoding transition. We use this scaling to formulate an adaptive buffer-selection rule and to identify a distance-scaled initialization for a composite quasi-local RG decoder on the full torus. In the tuned family $a_0=b_0=d/8$, the resulting logical-failure curves show an apparent finite-size crossing at $p\\simeq0.09$--$0.10$, below the conventional MWPM threshold scale. We focus on dephasing noise with perfect syndrome measurements to cleanly isolate the underlying behavior.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.27740",
  "author_total": 3,
  "authors": [
    {
      "name": "Hossein Dehghani"
    },
    {
      "name": "Sarang Gopalakrishnan"
    },
    {
      "name": "Michael Gullans"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/723t6d3jbf2w8.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.27740",
  "fulltext_url": null,
  "id": "723t6d3jbf2w8",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.27740",
  "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",
      "cond-mat.stat-mech"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
  ],
  "openalex": "W7204763341",
  "pdf_url": "https://arxiv.org/pdf/2608.27740",
  "pmcid": null,
  "pmid": null,
  "published": "2026-08-27",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/723t6d3jbf2w8.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:22Z",
      "native_id": "2608.27740",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.27740"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    },
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.stat-mech",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Error-Adaptive Quasi-local Decoding of the Toric Code",
  "title_text": "Error-Adaptive Quasi-local Decoding of the Toric Code",
  "type": "preprint",
  "updated_at": "2026-10-30T12:17:22Z",
  "url": "https://research.draconitic.com/paper/723t6d3jbf2w8",
  "venue": "arXiv",
  "versions": []
}