Experimental Adaptive Bayesian Tomography
classification
🪐 quant-ph
keywords
adaptiveapproachbayesianexperimentalscalingtomographyadaptedadvantage
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We report an experimental realization of an adaptive quantum state tomography protocol. Our method takes advantage of a Bayesian approach to statistical inference and is naturally tailored for adaptive strategies. For pure states we observe close to 1/N scaling of infidelity with overall number of registered events, while best non-adaptive protocols allow for $1/\sqrt{N}$ scaling only. Experiments are performed for polarization qubits, but the approach is readily adapted to any dimension.
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