Xu, Zhen-Peng

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Xu, Zhen-Peng

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    Quantum LOSR networks cannot generate graph states with high fidelity
    (2024)
    Wang, Yi-Xuan 
    ;
    Xu, Zhen-Peng 
    ;
    Gühne, Otfried 
    Quantum networks lead to novel notions of locality and correlations and an important problem concerns the question of which quantum states can be experimentally prepared with a given network structure and devices and which not. We prove that all multi-qubit graph states arising from a connected graph cannot originate from any quantum network with bipartite sources, as long as feed-forward and quantum memories are not available. Moreover, the fidelity of a multi-qubit graph state and any network state cannot exceed 9/10. Similar results can also be established for a large class of multi-qudit graph states.
    Source Type:Article
    DOI:https://doi.org/10.1038/s41534-024-00806-z
      12  64
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    PublicationAccess status: Open Access ,
    Symmetries in quantum networks lead to no-go theorems for entanglement distribution and to verification techniques
    (2022)
    Hansenne, Kiaraorcid-logo
    ;
    Xu, Zhen-Peng 
    ;
    Kraft, Tristan 
    ;
    Gühne, Otfried 
    Quantum networks are promising tools for the implementation of long-range quantum communication. The characterization of quantum correlations in networks and their usefulness for information processing is therefore central for the progress of the field, but so far only results for small basic network structures or pure quantum states are known. Here we show that symmetries provide a versatile tool for the analysis of correlations in quantum networks. We provide an analytical approach to characterize correlations in large network structures with arbitrary topologies. As examples, we show that entangled quantum states with a bosonic or fermionic symmetry can not be generated in networks; moreover, cluster and graph states are not accessible. Our methods can be used to design certification methods for the functionality of specific links in a network and have implications for the design of future network structures.
    Source Type:Article
    DOI:10.25819/ubsi/10236
      191  86