Conditional distributions, as defined by the Markov category framework, are studied in the setting of matrix algebras (quantum systems). Their construction as linear unital maps are obtained via a categorical Bayesian inversion procedure. Simple criteria establishing when such linear maps are positive are obtained. Several examples are provided, including the standard EPR scenario, where the EPR correlations are reproduced in a purely compositional (categorical) manner. A comparison between the Bayes map, the Petz recovery map, and the Leifer--Spekkens acausal belief propagation is provided, illustrating some similarities and key differences.
翻译:根据Markov类别框架的定义,在设置矩阵代数(量子系统)时研究条件分布,通过绝对的巴伊西亚反向程序,作为线性单位图进行构造,简单标准确定线性图为正数,提供若干例子,包括标准 EPR 设想,即EPR 相关关系纯粹以组成(分类)方式复制。Bayes 地图、Petz 恢复地图和Leifer-Spekkkens causal信仰传播之间的比较,说明一些相似之处和关键差异。