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Quantum Information Processing

Multi-nonlocality and detection of multipartite entanglements by special quantum networks

Li‐Hua Yang, Xiaofei Qi, Jinchuan Hou

Published Aug 20, 2022• 6 citations
Publisher
DOI
10.1007/s11128-022-03637-z

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The quantum entanglement as one of very important resources has been widely used in quantum information processing. In this work, we present a new kind of genuine multipartite entanglement. It is derived from special geometric feature of entangled systems compared with quantum multisource networks. We prove that any symmetric entangled pure state shows stronger nonlocality than the genuinely multipartite nonlocality in the biseparable model. Similar results hold for other entangled pure states with local dimensions no larger than 333. We further provide computational conditions for witnessing the new nonlocality of noisy states. These results suggest that the present model is useful characterizing a new kind of generic quantum entanglement.
Large-scale multisource networks have been employed to overcome the practical constraints that entangled systems are difficult to faithfully transmit over large distances or store over long times. However, a full characterization of the multipartite nonlocality of these networks remains out of reach, mainly due to the complexity of multipartite causal models. In this paper, we propose a general framework of Bayesian networks to reveal connections among different causal structures. The present model implies a special star-convex set of nonsignaling correlations from multisource networks that allows the construction of a polynomial-time algorithm for solving the compatibility problem of a given correlation distribution and a fixed causal network. It is then used to classify the nonlocality originating from the standard entanglement swapping of tripartite networks. Our model provides a unified device-independent information processing method for exploring the practical security against nonsignaling eavesdroppers in multisource quantum networks.