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.
In the local-Clifford shadow protocol, each measurement shotk∈ {1,
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.