Tahe lesson of causal discovery algorithms for quantum correlations: causal explanations of Bell-inequality violations require fine-tuning
Tahe lesson of causal discovery algorithms for quantum correlations: causal explanations of Bell-inequality violations require fine-tuning
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DOI：
10.1088/1367-2630/17/3/033002
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发表时间：
2015-03-03
影响因子：
3.3
通讯作者：
Spekkens, Robert W.
中科院分区：
文献类型：
--
作者：
Wood, Christopher J.;Spekkens, Robert W.
在机器学习和统计学领域，一个活跃的研究领域是因果发现算法的发展，其目的是从一组变量显示的相关性中推断出这些变量之间存在的因果关系。我们将其中一些算法应用于纠缠量子系统中出现的相关性。我们表明，它们不能区分满足贝尔不等式的相关性和违反贝尔不等式的相关性，因此它们不能公正地解释某些量子相关性的因果关系。尽管如此，通过调整因果推理的概念工具，我们可以表明，任何试图为违反贝尔不等式的非信号相关性提供因果解释的尝试都必须与这些算法的核心原则相矛盾，即变量之间观察到的统计独立性不应该通过因果参数的微调来解释。特别是，我们证明了对大多数因果机制进行这种微调的必要性，这些机制已被提议作为贝尔相关性的基础，包括
An active area of research in the fields of machine learning and statistics is the development of causal discovery algorithms, the purpose of which is to infer the causal relations that hold among a set of variables from the correlations that these exhibit. We apply some of these algorithms to the correlations that arise for entangled quantum systems. We show that they cannot distinguish correlations that satisfy Bell inequalities from correlations that violate Bell inequalities, and consequently that they cannot do justice to the challenges of explaining certain quantum correlations causally. Nonetheless, by adapting the conceptual tools of causal inference, we can show that any attempt to provide a causal explanation of nonsignalling correlations that violate a Bell inequality must contradict a core principle of these algorithms, namely, that an observed statistical independence between variables should not be explained by fine-tuning of the causal parameters. In particular, we demonstrate the need for such fine-tuning for most of the causal mechanisms that have been proposed to underlie Bell correlations, including