Characterising the correlations of prepare-and-measure quantum networks
This work addresses the need for versatile analysis tools in quantum communication and cryptography, offering incremental improvements by enabling efficient characterization of a wide range of quantum network protocols.
The authors tackled the problem of characterizing input-output probability distributions in prepare-and-measure quantum networks, developing a computational toolbox that efficiently handles discrete-variable networks using only inner-product information of quantum encodings, and demonstrated its feasibility by revealing new results in multipartite quantum distributed computing and quantum cryptography.
Prepare-and-measure (P&M) quantum networks are the basic building blocks of quantum communication and cryptography. These networks crucially rely on non-orthogonal quantum encodings to distribute quantum correlations, thus enabling superior communication rates and information-theoretic security. Here, we present a computational toolbox that is able to efficiently characterise the set of input-output probability distributions for any discrete-variable P&M quantum network, assuming only the inner-product information of the quantum encodings. Our toolbox is thus highly versatile and can be used to analyse a wide range of quantum network protocols, including those that employ infinite-dimensional quantum code 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 implications for quantum network information theory and the development of new quantum technologies.