{
  "abstract": "Near-term quantum and quantum-inspired solvers for portfolio optimization rely on local subproblem execution under severe size constraints, but this locality can omit cross-cluster covariance essential for global risk coordination. We propose Context-Aware Folding (CAF), a lightweight hybrid quantum-classical coordination layer between one-shot static decomposition and full-matrix optimization. CAF injects a compressed global risk state into each local subproblem via a state-dependent linear bias, decouples local candidate generation from global commitment, and retains a sequential acceptance rule with a monotonic non-divergence guarantee. On a 2016 Russell 3000 subset (N=484) with Simulated Annealing (SA), CAF improves the scalarized mean-variance objective by 6.59\\% over a static baseline (20/20 wins), and by 0.2579\\% on an additional 2018 panel (N=1397, 17/20 wins). We further report matched folded N=40 compatibility studies with the Quantum Approximate Optimization Algorithm (QAOA) and simulated quantum annealing (SQA) as local solvers, together with a frozen hardware-in-the-loop run on Origin Quantum's Wukong 180 (\\texttt{WK\\_C180}) for one warm-started QAOA subproblem at n=5. These results support CAF as a coordination architecture with strong classical large-scale evidence, cross-backend compatibility, and local executability on real quantum hardware in the noisy intermediate-scale quantum (NISQ) era.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "Journal reference: Proceedings of the 2026 IEEE International Conference on Quantum Computing and Engineering (QCE)",
  "arxiv": "2609.15708",
  "author_total": 3,
  "authors": [
    {
      "name": "Xiaoguang Yang"
    },
    {
      "name": "Menghan Dou"
    },
    {
      "name": "Guoping Guo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7f45823dkn9bk.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.15708",
  "fulltext_url": null,
  "id": "7f45823dkn9bk",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.15708",
  "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",
      "cs.CE"
    ],
    [
      "arxiv",
      "cs.ET"
    ],
    [
      "arxiv",
      "quant-ph"
    ],
    [
      "openalex",
      "1702|Quantum Computing Algorithms and Architecture"
    ]
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  "openalex": "W7213315836",
  "pdf_url": "https://arxiv.org/pdf/2609.15708",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-14",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/7f45823dkn9bk.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:22:19Z",
      "native_id": "2609.15708",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.15708"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "A Hybrid Quantum-Classical Coordination Architecture for Portfolio Optimization via Global Context Injection",
  "title_text": "A Hybrid Quantum-Classical Coordination Architecture for Portfolio Optimization via Global Context Injection",
  "type": "preprint",
  "updated_at": "2026-10-30T12:22:19Z",
  "url": "https://research.draconitic.com/paper/7f45823dkn9bk",
  "venue": "arXiv",
  "versions": []
}