Please use this identifier to cite or link to this item: https://doi.org/10.1038/s41534-019-0133-3
Title: Characterising the correlations of prepare-and-measure quantum networks
Authors: WANG YUKUN 
Primaatmaja, Ignatius William
Lavie, Emilien
VARVITSIOTIS ANTONIOS 
Lim, Charles Ci Wen
Keywords: Science & Technology
Physical Sciences
Quantum Science & Technology
Physics, Applied
Physics, Atomic, Molecular & Chemical
Physics, Condensed Matter
Physics
KEY DISTRIBUTION
SECURITY
PROTOCOL
CLONING
CANNOT
Issue Date: 8-Feb-2019
Publisher: SPRINGERNATURE
Citation: WANG YUKUN, Primaatmaja, Ignatius William, Lavie, Emilien, VARVITSIOTIS ANTONIOS, Lim, Charles Ci Wen (2019-02-08). Characterising the correlations of prepare-and-measure quantum networks. NPJ QUANTUM INFORMATION 5 (1). ScholarBank@NUS Repository. https://doi.org/10.1038/s41534-019-0133-3
Abstract: It is well known that transmitting classical information over quantum networks can significantly improve communication rates and achieve secure communication. These quantum advantages crucially rely on the network's innate ability to distribute classical correlations reliably and securely. To this end, it is of significant interest to understand how classical information propagates in quantum networks. Here, we report a computational toolbox that is able to characterise the stochastic matrix of any classical-quantum network, assuming only the inner-product information of the quantum code states. The toolbox is hence highly versatile and can analyse a wide range of quantum network protocols, including those that employ infinite-dimensional quantum states. To demonstrate the feasibility and efficacy of our toolbox, we use it to reveal new results in multipartite quantum distributed computing and quantum cryptography. Taken together, these findings suggest that our method may have important implications for quantum network information theory and the development of new quantum technologies.
Source Title: NPJ QUANTUM INFORMATION
URI: https://scholarbank.nus.edu.sg/handle/10635/157463
ISSN: 2056-6387
DOI: 10.1038/s41534-019-0133-3
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