{
  "abstract": "The feedback-based algorithm for quantum optimization (FALQON), which is an extension of the quantum approximate optimization algorithm (QAOA), is a promising approach for finding approximate solutions to combinatorial optimization problems. The FALQON avoids the optimization of variational parameters by using information derived from iterative measurements. To solve a constrained combinatorial optimization problem, it is sometimes more efficient to use an XY mixer rather than the conventional X mixer. We applied the FALQON with the XY mixer to graph coloring and investigated the expectation value of the problem Hamiltonian, success probability of graph coloring, and fair sampling for several small-scale problems. The FALQON with the XY mixer exhibited better performance than that with the X mixer.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.30991",
  "author_total": 3,
  "authors": [
    {
      "name": "Yuika Kawatomi"
    },
    {
      "name": "Yukina Tatsuta"
    },
    {
      "name": "Kazue Kudo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dtfqsafjhgkc5.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.30991",
  "fulltext_url": null,
  "id": "dtfqsafjhgkc5",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.30991",
  "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": "W7214680293",
  "pdf_url": "https://arxiv.org/pdf/2609.30991",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-25",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/dtfqsafjhgkc5.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:24:52Z",
      "native_id": "2609.30991",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.30991"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    }
  ],
  "title": "Solving Graph Coloring Problems Using Feedback-Based Algorithm for Quantum Optimization",
  "title_text": "Solving Graph Coloring Problems Using Feedback-Based Algorithm for Quantum Optimization",
  "type": "preprint",
  "updated_at": "2026-10-30T12:24:52Z",
  "url": "https://research.draconitic.com/paper/dtfqsafjhgkc5",
  "venue": "arXiv",
  "versions": []
}