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    "headline": "The Circuit Description Explained Most of the Mitigation Gain",
    "slug": "the-circuit-description-explained-most-of-the-mitigation-gain",
    "dek": "Capacity-matched controls reproduced 87.7–100.5% of selected learners' gain in familiar simulated regimes.",
    "summary": "Capacity-matched controls reproduced 87.7–100.5% of selected learners' gain in familiar simulated regimes.",
    "body_text": "Learned quantum error mitigation can appear successful even when a model mostly reads circuit structure rather than the noisy measurement. QEMScore pairs each mitigator with an equally flexible control that never sees the measurement. Across two simulated spin-chain families and three seeds, those controls matched 87.7% to 100.5% of the selected mitigators' gain over an affine descriptor fit; a polynomial descriptor model beat the mitigator in all six evaluations. Released Q-LEAR and QRAFT hardware data differed, with measurement inputs adding predictive value. The paper argues that mitigation results need capacity-matched no-measurement controls.",
    "why_it_matters": "Capacity-matched controls reproduced 87.7–100.5% of selected learners' gain in familiar simulated regimes.",
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    "importance": 8,
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    "first_published_at": "2026-09-17T09:00:00.000-04:00",
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        "text": "Capacity-matched controls reproduced 87.7–100.5% of selected learners' gain in familiar simulated regimes.",
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    "tags": [
      "quantum error mitigation",
      "benchmark controls",
      "measurement"
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      "source_id": "source-2026-09-17-013",
      "title": "arXiv preprint 2609.17896",
      "publisher": "arXiv",
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      "published_at": "2026-09-15T18:39:09.000-04:00",
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    "name": "The Machine Press",
    "url": "https://themachinepress.com",
    "description": "A daily newspaper for the age of artificial intelligence."
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    "title": "The Circuit Description Explained Most of the Mitigation Gain",
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