论文标题
连续分布家族中网络量子非局部性的证明
Proofs of network quantum nonlocality in continuous families of distributions
论文作者
论文摘要
在远离双方爱因斯坦 - 波多尔斯基 - 罗森 - 罗森 - 罗森特设置的情况下，非局部性的研究允许揭示量子力学的许多基本特征。最近，一种基于机器学习建立网络本地模型的方法导致猜想，即[Arxiv：1905.04902]的量子三角分布家族并未接纳比原始证明更大的三角形 - 局部模型。我们在肯定中证明了这一猜想的一部分。我们的方法包括将原始的四项结果分布的家族减少到二元期为家族的家族，然后使用通货膨胀技术证明这些二元 - 结果分布家族不承认三角局部模型。这构成了通货膨胀在网络中首次成功使用通货膨胀证明，其非局部性无法通过替代方法证明。此外，我们提供了一种方法，以扩展参数化家族的具体分布中网络非局部性的证明，以扩展参数的连续范围。在此过程中，我们为具有二元结果的三角形情况产生了大量的网络铃铛不平等现象，这些结果具有独立的兴趣。
The study of nonlocality in scenarios that depart from the bipartite Einstein-Podolsky-Rosen setup is allowing to uncover many fundamental features of quantum mechanics. Recently, an approach to building network-local models based on machine learning lead to the conjecture that the family of quantum triangle distributions of [arXiv:1905.04902] did not admit triangle-local models in a larger range than the original proof. We prove part of this conjecture in the affirmative. Our approach consists in reducing the family of original, four-outcome distributions to families of binary-outcome ones, and then using the inflation technique to prove that these families of binary-outcome distributions do not admit triangle-local models. This constitutes the first successful use of inflation in a proof of quantum nonlocality in networks whose nonlocality could not be proved with alternative methods. Moreover, we provide a method to extend proofs of network nonlocality in concrete distributions of a parametrized family to continuous ranges of the parameter. In the process, we produce a large collection of network Bell inequalities for the triangle scenario with binary outcomes, which are of independent interest.
