Year: 2020
Type: article
Abstract: 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.
Source: Physical Review A
Author: Ming-Xing Luo
Institution: Southwest Jiaotong University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2885807646