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Physical Review Letters
Article . 2020 . Peer-reviewed
License: CC BY
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Physical Review Letters
Article
License: CC BY
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https://dx.doi.org/10.48550/ar...
Article . 2020
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
Physical Review Letters
Article . 2020 . Peer-reviewed
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Ultimate Limits for Multiple Quantum Channel Discrimination

Authors: Zhuang, Quntao; Pirandola, Stefano;

Ultimate Limits for Multiple Quantum Channel Discrimination

Abstract

Quantum hypothesis testing is a central task in the entire field of quantum information theory. Understanding its ultimate limits will give insight into a wide range of quantum protocols and applications, from sensing to communication. Although the limits of hypothesis testing between quantum states have been completely clarified by the pioneering works of Helstrom in the 70s, the more difficult problem of hypothesis testing with quantum channels, i.e., channel discrimination, is less understood. This is mainly due to the complications coming from the use of input entanglement and the possibility of employing adaptive strategies. In this paper, we establish a lower limit for the ultimate error probability affecting the discrimination of an arbitrary number of quantum channels. We also show that this lower bound is achievable when the channels have certain symmetries. As an example, we apply our results to the problem of channel position finding, where the goal is to identify the location of a target channel among multiple background channels. In this general setting, we find that the use of entanglement offers a great advantage over strategies without entanglement, with non-trivial implications for data readout, target detection and quantum spectroscopy.

6+12 pages, 6 figures

Country
United Kingdom
Keywords

Quantum Physics, quant-ph, FOS: Mathematics, stat.TH, FOS: Physical sciences, Mathematics - Statistics Theory, Statistics Theory (math.ST), math.ST, Quantum Physics (quant-ph)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Top 10%
Green
hybrid