星形网络非n-局域关联能更好地抵抗一致性噪声
Star network non-n-local correlations can resist consistency noises better
AI总结：
本文发现星形网络量子非n-局域关联比多边形和线性网络更能抵抗一致性噪声，其源数量持久性趋近无穷，并研究了部分一致性噪声下最大源数量的变化规律。
摘要：
设备的不完美会导致多边形和线性量子网络（[Phys. Rev. A 106, 042206 (2022)] 和 [Phys. Rev. A 107, 032404 (2023)]）中，随着参与方数量n的增加，非n-局域关联发生衰减甚至消失。这一现象同样适用于特殊类型的噪声，包括一系列设备的一致性噪声，即设备序列具有相同的检测失败概率。然而，在本文中，我们发现星形网络量子非n-局域关联比多边形和线性网络中的关联能更好地抵抗一致性噪声。我们首先计算了星形网络非n-局域性的噪声期望值，并从理论上分析了其持久性条件。当假设同类设备具有一致性噪声时，源的数量n的持久性已摆脱此类噪声的影响，并趋近于无穷大。多边形和线性网络的非n-局域关联无法满足这些要求。此外，我们探讨了在部分一致性噪声（比一致性噪声更普遍）的影响下，星形网络中能够展示非n_max-局域关联的最大源数量n_max的变化模式。
英文摘要：
Imperfections from devices can result in the decay or even vanish of non-n-local correlations as the number of parties n increases in the polygon and linear quantum networks ([Phys. Rev. A 106, 042206 (2022)] and [Phys. Rev. A 107, 032404 (2023)]). Even so this phenomenon is also for the special kind of noises, including consistency noises of a sequence of devices, which means the sequence of devices have the same probability fails to detect. However, in the paper, we discover that star network quantum non-n-local correlations can resist better consistency noises than these in polygon and linear networks. We first calculate the noisy expected value o f star network non-n-locality and analyze the persistency conditions theoretically. When assume that congener devices have the consistency noise, the persistency number of sources n has been rid of such noises, and approximates to the infinity. Polygon and linear network non-n-local correlations can not meet the requirements. Furthermore, we explore the change pattern of the maximal number of sources nmax such that non-nmax-local correlation can be demonstrated in the star network under the influence of partially consistent noises, which is more general than consistent ones.
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