论文标题
因果网络中的实验性非经典性而不假设选择自由
Experimental nonclassicality in a causal network without assuming freedom of choice
论文作者
论文摘要
在贝尔实验中，自然而然地寻求因果关系的因果关系，其中只有一个共同的原因对结果作用。对于这种因果结构，只有在因果依赖性本质上建模为量子时，才能解释贝尔不平等的违规行为。在贝尔之外，还存在广阔的因果结构景观，在某些情况下甚至不需要免费的外部投入。在这里，我们进行了一个光子实验，意识到一个这样的例子：三角因果网络，由三个测量站组成，由共同原因和无外部输入连接。为了证明数据的非经典性，我们适应并改善了三种已知技术：（i）基于机器学习的启发式测试，（ii）产生多项式钟形不平等和（iii）熵不平等的数据种子通货膨胀技术。所证明的实验和数据分析工具广泛适用，为未来的复杂性网络铺平了道路。
In a Bell experiment, it is natural to seek a causal account of correlations wherein only a common cause acts on the outcomes. For this causal structure, Bell inequality violations can be explained only if causal dependencies are modelled as intrinsically quantum. There also exists a vast landscape of causal structures beyond Bell that can witness nonclassicality, in some cases without even requiring free external inputs. Here, we undertake a photonic experiment realizing one such example: the triangle causal network, consisting of three measurement stations pairwise connected by common causes and no external inputs. To demonstrate the nonclassicality of the data, we adapt and improve three known techniques: (i) a machine-learning-based heuristic test, (ii) a data-seeded inflation technique generating polynomial Bell-type inequalities and (iii) entropic inequalities. The demonstrated experimental and data analysis tools are broadly applicable paving the way for future networks of growing complexity.
