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Cited by 485

The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index.

Microwave Quantum Illumination

Open access
Barzanjeh, Shabir, Guha, Saikat, Weedbrook, Christian, Vitali, David, Shapiro, Jeffrey H., Pirandola, Stefano·2015·Physical Review Letters

Abstract

Quantum illumination is a quantum-optical sensing technique in which an entangled source is exploited to improve the detection of a low-reflectivity object that is immersed in a bright thermal background. Here, we describe and analyze a system for applying this technique at microwave frequencies, a more appropriate spectral region for target detection than the optical, due to the naturally occurring bright thermal background in the microwave regime. We use an electro-optomechanical converter to entangle microwave signal and optical idler fields, with the former being sent to probe the target region and the latter being retained at the source. The microwave radiation collected from the target region is then phase conjugated and upconverted into an optical field that is combined with the retained idler in a joint-detection quantum measurement. The error probability of this microwave quantum-illumination system, or quantum radar, is shown to be superior to that of any classical microwave radar of equal transmitted energy.

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Metadata

Authors
Barzanjeh, S., Guha, S., Weedbrook, C., Vitali, D., Shapiro, J. H., & Pirandola, S.
Venue
Physical Review Letters
Published
2015-02-27
Volume
114
Issue
8
Pages
080503-080503
ISSN
  • 0031-9007 (ISSN-L)
  • 1079-7114
OpenAlex
W1977248165
Cited by
485
References
47
FWCI
31.91
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Microwave Quantum Illumination. https://app.cochat.ai/papers/10.1103/physrevlett.114.080503
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Barzanjeh, S., Guha, S., Weedbrook, C., Vitali, D., Shapiro, J. H., & Pirandola, S. (2015). Microwave Quantum Illumination. Physical Review Letters. https://doi.org/10.1103/physrevlett.114.080503

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.