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.
What remains is only the subtraction term from the mean, yielding: R(∆) n,p =− 4−nq nc δn,p.(F23) Thus the residual pseudo-covariance is diagonal and exponentially small innq
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
quant-ph 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.