Publication | Open Access
Information amplification via postselection: A parameter-estimation perspective
118
Citations
24
References
2013
Year
EngineeringMeasurementUsual Quantum MeasurementQuantum MeasurementText MiningMeasurement ProblemNatural Language ProcessingInformation RetrievalQuantum ComputingUncertainty QuantificationComputational LinguisticsQuantum EntanglementEstimation TheoryStatisticsInformation TheoryLower BoundKnowledge DiscoveryInformation AmplificationInformation ExtractionInformation StructureUncertainty PrincipleWeak MeasurementStatistical Inference
It is known that weak measurement can significantly amplify the mean of measurement results, sometimes out of the range limited in usual quantum measurement. This fact, as actively demonstrated recently in both theory and experiment, implies the possibility to estimate a very small parameter using the weak measurement technique. But does the weak measurement really bring about the increase of ``information'' for parameter estimation? This paper clarifies that, in a general situation, the answer is NO; more precisely, the weak measurement cannot further decrease the lower bound of the estimation error, i.e., the so-called Cram\'er-Rao bound, which is proportional to the inverse of the quantum Fisher information.
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