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Since the numerical study is performed in the gaugey= 0nq, Hamming shells around the target locationyare indexed simply by the Hamming weight of the intermediate bit stringt

Hamming-shell feature families We now define the feature maps used by the classifier in terms of the reduced shadow representation{rt, ct, dt}

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Evidence of Quantum Machine Learning Advantage with Tens of Noisy Qubits

quant-ph · 2026-05-20 · conditional · novelty 6.0

Simulations of a known quantum learning task demonstrate clear performance separation between coherent noisy quantum processing and fixed-measurement classical strategies at 30-40 qubits, with data acquisition as the primary bottleneck.

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  • Evidence of Quantum Machine Learning Advantage with Tens of Noisy Qubits quant-ph · 2026-05-20 · conditional · none · ref 29

    Simulations of a known quantum learning task demonstrate clear performance separation between coherent noisy quantum processing and fixed-measurement classical strategies at 30-40 qubits, with data acquisition as the primary bottleneck.