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    "story_id": "mp-2026-08-21-026",
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    "headline": "The Quantum Model Reached Similar Accuracy by a Different Route",
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    "dek": "A 125-parameter hybrid forecaster matched a 281-parameter classical baseline while showing distinct kernel dynamics.",
    "summary": "A 125-parameter hybrid forecaster matched a 281-parameter classical baseline while showing distinct kernel dynamics.",
    "body_text": "On controlled harmonic and chirp forecasting tasks, the classical model aligned with targets earlier while the hybrid quantum model developed a less concentrated kernel spectrum and smaller drift. Held-out performance remained similar, and the hybrid system reached its selected checkpoint earlier in 15 of 18 frequency conditions with fewer trainable parameters. The authors explicitly do not claim quantum advantage; the result is about learning geometry hidden by endpoint accuracy.",
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      "The authors explicitly do not claim quantum advantage; the result is about learning geometry hidden by endpoint accuracy."
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    "tags": [
      "quantum machine learning",
      "forecasting",
      "neural tangent kernels"
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      "source_id": "source-2026-08-21-015",
      "title": "arXiv preprint 2608.19497",
      "publisher": "arXiv",
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      "published_at": "2026-08-18T20:00:00.000-04:00",
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    "title": "The Quantum Model Reached Similar Accuracy by a Different Route",
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