Final Published Version
AffiliationUniversity of Arizona, Department of Electrical and Computer Engineering
Entanglement-based hybrid QKD
Hybrid CV-DV entangled states
Hybrid power systems
Hybrid quantum communication networks
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CitationDjordjevic, I. B. (2022). Hybrid CV-DV Quantum Communications and Quantum Networks. IEEE Access.
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AbstractQuantum information processing (QIP) opens new opportunities for high-performance computing, high-precision sensing, and secure communications. Among various QIP features, the entanglement is a unique one. To take full advantage of quantum resources, it will be necessary to interface quantum systems based on different encodings of information both discrete and continuous. The goal of this paper is to lay the groundwork for the development of a robust and efficient hybrid continuous variable-discrete variable (CV-DV) quantum network, enabling the distribution of a large number of entangled states over hybrid DV-CV multi-hop nodes in an arbitrary topology. The proposed hybrid quantum communication network (QCN) can serve as the backbone for a future quantum Internet, thus providing extensive long-term impacts on the economy and national security through QIP, distributed quantum computing, quantum networking, and distributed quantum sensing. By employing the photon addition and photon subtraction modules we describe how to generate the hybrid DV-CV entangled states and how to implement their teleportation and entanglement swapping through entangling measurements. We then describe how to extend the transmission distance between nodes in hybrid QCN by employing macroscopic light states, noiseless amplification, and reconfigurable quantum LDPC coding. We further describe how to enable quantum networking and distributed quantum computing by employing the deterministic cluster state concept introduced here. Finally, we describe how the proposed hybrid CV-DV states can be used in an entanglement-based hybrid QKD. Author
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Except where otherwise noted, this item's license is described as Copyright © 2022 IEEE. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
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