Affiliation
Univ Arizona, Dept Elect & Comp EngnUniv Arizona, James C Wyant Coll Opt Sci
Issue Date
2020-06-02
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NATURE PUBLISHING GROUPCitation
Zhuang, Q., Pirandola, S. Entanglement-enhanced testing of multiple quantum hypotheses. Commun Phys 3, 103 (2020). https://doi.org/10.1038/s42005-020-0369-4Journal
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Copyright © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Quantum channel discrimination exploits quantum resources to improve hypothesis testing for binary bosonic channels. Here, the authors overcome the binary setting, showing quantum entanglement greatly enhances the discrimination performance for an arbitrary number of channels. Quantum hypothesis testing has been greatly advanced for the binary discrimination of two states, or two channels. In this setting, we already know that quantum entanglement can be used to enhance the discrimination of two bosonic channels. Here, we remove the restriction of binary hypotheses and show that entangled photons can remarkably boost the discrimination of multiple bosonic channels. More precisely, we formulate a general problem of channel-position finding where the goal is to determine the position of a target channel among many background channels. We prove that, using entangled photons at the input and a generalized form of conditional nulling receiver at the output, we may outperform any classical strategy. Our results can be applied to enhance a range of technological tasks, including the optical readout of sparse classical data, the spectroscopic analysis of a frequency spectrum, and the determination of the direction of a target at fixed range.Note
Open access journalISSN
2399-3650Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1038/s42005-020-0369-4
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Except where otherwise noted, this item's license is described as Copyright © The Author(s) 2020. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License.