
1.James C. Wyant College of Optical Sciences, University of Arizona, Tucson, AZ, 85721, USA
2.Department of Materials Science and Engineering, University of Arizona, Tucson, AZ, 85721, USA
3.Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, 85721, USA
4.Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA, 90089, USA
5.Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, 48109, USA
Zheshen Zhang (zszh@umich.edu)
Published:31 December 2022,
Published Online:08 December 2022,
Received:13 July 2022,
Revised:08 November 2022,
Accepted:16 November 2022
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Cui, C. H. et al. Quantum receiver enhanced by adaptive learning. Light: Science & Applications, 11, 3080-3086 (2022).
Cui, C. H. et al. Quantum receiver enhanced by adaptive learning. Light: Science & Applications, 11, 3080-3086 (2022). DOI: 10.1038/s41377-022-01039-5.
Quantum receivers aim to effectively navigate the vast quantum-state space to endow quantum information processing capabilities unmatched by classical receivers. To date
only a handful of quantum receivers have been constructed to tackle the problem of discriminating coherent states. Quantum receivers designed by analytical approaches
however
are incapable of effectively adapting to diverse environmental conditions
resulting in their quickly diminishing performance as the operational complexities increase. Here
we present a general architecture
dubbed the quantum receiver enhanced by adaptive learning
to adapt quantum receiver structures to diverse operational conditions. The adaptively learned quantum receiver is experimentally implemented in a hardware platform with record-high efficiency. Combining the architecture and the experimental advances
the error rate is reduced up to 40% over the standard quantum limit in two coherent-state encoding schemes.
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