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    "headline": "Eleven Million Cells Keep the Same Clusters",
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    "dek": "A training-free quantum-classical encoding produced identical runs and processed whole-transcriptome atlases on one server.",
    "summary": "A training-free quantum-classical encoding produced identical runs and processed whole-transcriptome atlases on one server.",
    "body_text": "KQE-2 maps cells to entanglement-free quantum states whose features can be evaluated exactly on classical hardware and checked on a quantum processor. The authors report that retraining scVI moved 14 percent of cells, while KQE-2 returned identical biological groupings across runs. Its encoding raised accuracy on a developing-cortex dataset from 0.61 to 0.79 and scaled to 11.4 million nuclei on one server, leading eight of ten complete atlases and staying within the best method's run-to-run range on the other two. These are preprint benchmark results, not evidence of quantum hardware speedup.",
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      "These are preprint benchmark results, not evidence of quantum hardware speedup."
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    "tags": [
      "single-cell genomics",
      "clustering",
      "quantum encoding"
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      "title": "arXiv preprint 2611.11745, original v1",
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