Issue |
EPL
Volume 114, Number 1, April 2016
|
|
---|---|---|
Article Number | 10005 | |
Number of page(s) | 6 | |
Section | General | |
DOI | https://doi.org/10.1209/0295-5075/114/10005 | |
Published online | 26 April 2016 |
Efficient superdense coding in the presence of non-Markovian noise
1 Key Laboratory of Quantum Information, University of Science and Technology of China, CAS Hefei, 230026, China
2 Synergetic Innovation Center of Quantum Information and Quantum Physics, University of Science and Technology of China, CAS, Hefei, 230026, China
3 Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku FI-20014 Turun yliopisto, Finland
4 Dipartimento di Fisica and INFN-Sezione di Pavia - via Bassi 6, I-27100 Pavia, Italy
(a) cfli@ustc.edu.cn
(b) jyrki.piilo@utu.fi
Received: 17 February 2016
Accepted: 15 April 2016
Many quantum information tasks rely on entanglement, which is used as a resource, for example, to enable efficient and secure communication. Typically, noise, accompanied by loss of entanglement, reduces the efficiency of quantum protocols. We develop and demonstrate experimentally a superdense coding scheme with noise, where the decrease of entanglement in Alice's encoding state does not reduce the efficiency of the information transmission. Having an almost fully dephased classical two-photon polarization state at the time of encoding with concurrence of , we reach values of mutual information close to with 3-state (4-state) encoding. This high efficiency relies both on non-Markovian features, that Bob exploits just before his Bell state measurement, and on very high visibility of the Hong-Ou-Mandel interference within the experimental set-up. Our proof-of-principle results with measurements on mutual information pave the way for exploiting non-Markovianity to improve the efficiency and security of quantum information processing tasks.
PACS: 03.65.Yz – Decoherence; open systems; quantum statistical methods / 42.50.-p – Quantum optics / 03.67.-a – Quantum information
© EPLA, 2016
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