Quantum mass functions (QMFs), which are tightly related to decoherence functionals, were introduced by Loeliger and Vontobel [IEEE Trans. Inf. Theory, 2017, 2020] as a generalization of probability mass functions toward modeling quantum information processing setups in terms of factor graphs. Simple quantum mass functions (SQMFs) are a special class of QMFs that do not explicitly model classical random variables. Nevertheless, classical random variables appear implicitly in an SQMF if some marginals of the SQMF satisfy some conditions; variables of the SQMF corresponding to these "emerging" random variables are called classicable variables. Of particular interest are jointly classicable variables. In this paper we initiate the characterization of the set of marginals given by the collection of jointly classicable variables of a graphical model and compare them with other concepts associated with graphical models like the sets of realizable marginals and the local marginal polytope. In order to further characterize this set of marginals given by the collection of jointly classicable variables, we generalize the CHSH inequality based on the Pearson correlation coefficients, and thereby prove a conjecture proposed by Pozsgay et al. A crucial feature of this inequality is its nonlinearity, which poses difficulties in the proof.
翻译:Loeliger和Vontobel[IEEE Trans.Inf.Theory, 2017, 2020] 引入了与脱不一致功能密切相关的量子质量函数(QMFs),作为概率质量函数的概括,以根据系数图解建模量信息处理设置模型。简单量子质量函数(SQMFs)是一个特殊的QMF类,并不明确地模拟典型随机变量。然而,如果SQMF的某些边缘满足某些条件,典型随机变量就隐含在SQMF中。SMF中与这些“正在出现”随机变量相对应的变量变数被称为可变数。特别感兴趣的变量是共同可变数变量。在本文件中,我们开始对一组边际参数进行定性,通过收集共同可复制的图形模型变量,将它们与其他与图形模型相关的概念进行比较,例如可变现边际边际变量和本地边际多功能。为了进一步描述共同可变数集的这一组的边际变量的边际变量,我们根据“CSH”不平等性变数加以概括化,根据关键特征和正正正正正正方形的亚等的模型,用该模型来验证。