Physical Review Applied · 2023 · 23 citations · 58 references
ComputingComputer SciencePhysicsPhotonicsQuantum ComputingQuantum MechanicsQuantum AlgorithmsQuantum ComputationQuantum Information TheoryQuantum Machine LearningQuantum MeasurementQuantum OpticsPhotonic Quantum Computing ArchitecturesPost-processingQuantum AdvantageQuantum Learning TheoryQuantum Machine Learning AlgorithmsQuantum Photonic Circuits
This work demonstrates experimentally that the advantage gained in sensing using quantum photonic resources can be sustained, and even amplified, through complex classical post-processing aimed at extracting relevant features. Despite the very different architectures of the classical algorithms tested here, the quantum advantage in classification performance appears to be robust and qualitatively very consistent. Thus the results argue for widespread use of quantum sensing technologies, in any field that deals with pattern recognition in large datasets.
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Gradient-based learning applied to document recognition
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