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Quantum advantage in postselected metrology

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Author(s)
Arvidsson-Shukur, David RM
•
Yunger Halpern, Nicole
•
Lepage, Hugo V
•
Lasek, Aleksander A
•
Barnes, Crispin HW
•
Lloyd, Seth
Date Issued
July 2020
Journal
Nature Communications
Publisher
Springer Science and Business Media LLC
Citation
Arvidsson-Shukur, David RM, Yunger Halpern, Nicole, Lepage, Hugo V, Lasek, Aleksander A, Barnes, Crispin HW et al. 2020. "Quantum advantage in postselected metrology." Nature Communications, 11 (1).
Version
Final published version
Abstract
© 2020, The Author(s). In every parameter-estimation experiment, the final measurement or the postprocessing incurs a cost. Postselection can improve the rate of Fisher information (the average information learned about an unknown parameter from a trial) to cost. We show that this improvement stems from the negativity of a particular quasiprobability distribution, a quantum extension of a probability distribution. In a classical theory, in which all observables commute, our quasiprobability distribution is real and nonnegative. In a quantum-mechanically noncommuting theory, nonclassicality manifests in negative or nonreal quasiprobabilities. Negative quasiprobabilities enable postselected experiments to outperform optimal postselection-free experiments: postselected quantum experiments can yield anomalously large information-cost rates. This advantage, we prove, is unrealizable in any classically commuting theory. Finally, we construct a preparation-and-postselection procedure that yields an arbitrarily large Fisher information. Our results establish the nonclassicality of a metrological advantage, leveraging our quasiprobability distribution as a mathematical tool.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Massachusetts Institute of Technology. Research Laboratory of Electronics
Terms of Use
Creative Commons Attribution 4.0 International license
https://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/138867.2
DOI of Published Version
https://doi.org/10.1038/S41467-020-17559-W
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