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量子加速因果关系识别。

Quantum speedup in the identification of cause-effect relations.

机构信息

Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong.

Department of Computer Science, University of Oxford, Oxford, OX1 3QD, UK.

出版信息

Nat Commun. 2019 Apr 1;10(1):1472. doi: 10.1038/s41467-019-09383-8.

Abstract

The ability to identify cause-effect relations is an essential component of the scientific method. The identification of causal relations is generally accomplished through statistical trials where alternative hypotheses are tested against each other. Traditionally, such trials have been based on classical statistics. However, classical statistics becomes inadequate at the quantum scale, where a richer spectrum of causal relations is accessible. Here we show that quantum strategies can greatly speed up the identification of causal relations. We analyse the task of identifying the effect of a given variable, and we show that the optimal quantum strategy beats all classical strategies by running multiple equivalent tests in a quantum superposition. The same working principle leads to advantages in the detection of a causal link between two variables, and in the identification of the cause of a given variable.

摘要

识别因果关系的能力是科学方法的一个基本组成部分。因果关系的识别通常是通过统计试验来完成的,在这些试验中,相互对照替代假设。传统上,这种试验是基于经典统计学的。然而,经典统计学在量子尺度上变得不够用了,因为在量子尺度上,可以获得更丰富的因果关系谱。在这里,我们表明量子策略可以大大加快因果关系的识别。我们分析了识别给定变量影响的任务,并且表明,通过在量子叠加中运行多个等效测试,最优的量子策略击败了所有经典策略。相同的工作原理导致在检测两个变量之间的因果关系以及识别给定变量的原因方面具有优势。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba9a/6443664/1882bd727a8e/41467_2019_9383_Fig1_HTML.jpg

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