用上下文轮廓分析系统在不同层次上的上下文性，揭示其复杂性结构。
Degrees, Levels, and Profiles of Contextuality
- 通过分层分析，将上下文性表现为随层次变化的曲线。
- 不同层次下，系统表现出不同的上下文性程度，揭示隐藏模式。
- 适用于多种测量方法，适合研究量子非局域性与认知科学中的系统行为。
我们提出系统随机变量的上下文性轮廓新概念。不同于传统以单一数值表征整体上下文性的做法，本文通过曲线展示上下文性随系统考虑层次的变化关系：第n层指仅关注最多n个变量的联合分布，忽略更高阶联合分布。该层次化分析可与任意合理的上下文性度量结合使用。我们提出串联系统方法，系统性探索三种文献中主要上下文性度量的轮廓，并验证其有效性。
原文摘要 · Abstract (English)
We introduce a new notion, that of a contextuality profile of a system of random variables. Rather than characterizing a system's contextuality by a single number, its overall degree of contextuality, we show how it can be characterized by a curve relating degree of contextuality to level at which the system is considered. A system is represented at level n if one only considers the joint distributions with no more than n variables, ignoring higher-order joint distributions. We show that the level-wise contextuality analysis can be used in conjunction with any well-constructed measure of contextuality. We present a method of concatenated systems to explore contextuality profiles systematically, and we apply it to the contextuality profiles for three major measures of contextuality proposed in the literature.
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