{
  "abstract": "Fast, high-fidelity qubit initialization is a key primitive for scalable quantum information processing, but conventional reset protocols either require long relaxation times or discard information contained in continuous measurement records. We demonstrate an adaptive measurement-based reset protocol for superconducting qubits that uses Bayesian inference to update the qubit-state estimate after each readout and dynamically adjust the feedback threshold. Unlike fixed-threshold or repeat-until-success (RUS) protocols, the method utilizes the full analog measurement history, enabling the reset decision to become progressively more conservative as confidence in ground-state preparation increases. Implemented with real-time FPGA-based feedback on a dispersively readout transmon qubit, the protocol achieves a ground-state initialization fidelity of $99.44\\pm0.04\\%$ after a small number of reset rounds. We further compare adaptive reset with RUS strategies in multi-qubit experiments and show that adaptive thresholding provides deterministic reset duration while maintaining a five-qubit simultaneous-reset fidelity of $98.78 \\pm 0.19\\%$. These results establish Bayesian adaptive thresholding as a practical and scalable route to fast qubit reset in superconducting quantum processors.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.25208",
  "author_total": 6,
  "authors": [
    {
      "name": "Qian Cao"
    },
    {
      "name": "Unnati Akhouri"
    },
    {
      "name": "Samuel Vizvary"
    },
    {
      "name": "Nissim Ofek"
    },
    {
      "name": "Wei Dai"
    },
    {
      "name": "Kater W. Murch"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/6qk33b4asvzgf.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.25208",
  "fulltext_url": null,
  "id": "6qk33b4asvzgf",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.25208",
  "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 Information and Cryptography"
    ]
  ],
  "openalex": "W7214123169",
  "pdf_url": "https://arxiv.org/pdf/2609.25208",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-21",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/6qk33b4asvzgf.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:23:39Z",
      "native_id": "2609.25208",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.25208"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:quant-ph",
      "subfield": "quantum"
    },
    {
      "field": "physics",
      "origin": "arxiv:cond-mat.stat-mech",
      "subfield": "statistical-nonlinear"
    }
  ],
  "title": "Adaptive thresholding for scalable measurement-based qubit reset",
  "title_text": "Adaptive thresholding for scalable measurement-based qubit reset",
  "type": "preprint",
  "updated_at": "2026-10-30T12:23:39Z",
  "url": "https://research.draconitic.com/paper/6qk33b4asvzgf",
  "venue": "arXiv",
  "versions": []
}