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.
This motivates the decomposition of the register into: A(α) :={i:α i = 1},P(α) :={i:α i = 0},(D4) with|A|=|α|
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Evidence of Quantum Machine Learning Advantage with Tens of Noisy Qubits
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.