4.8 Article

Ultimate Limits for Multiple Quantum Channel Discrimination

Journal

PHYSICAL REVIEW LETTERS
Volume 125, Issue 8, Pages -

Publisher

AMER PHYSICAL SOC
DOI: 10.1103/PhysRevLett.125.080505

Keywords

-

Funding

  1. Army Research Office [W911NF-19-1-0418]
  2. European Union's Horizon 2020 Research and Innovation Action [862644]
  3. Office of Naval Research [N00014-19-1-2189]
  4. Defense Advanced Research Projects Agency (DARPA) under Young Faculty Award (YFA) Grant [N660012014029]
  5. University of Arizona

Ask authors/readers for more resources

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 1970s, 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 Letter, 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 nontrivial implications for data readout, target detection, and quantum spectroscopy.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available