论文标题
通货膨胀：用于经典和量子因果兼容性的Python库
Inflation: a Python library for classical and quantum causal compatibility
论文作者
论文摘要
我们介绍了通货膨胀，这是一个用于评估观察到的概率分布是否与因果解释兼容的Python文库。这在理论和应用科学中都是一个核心问题，最近在通货膨胀技术的发展中，它最近见证了量子非局部性领域的重大进展。通货膨胀是一种可扩展的工具包，能够解决纯粹的因果兼容性问题并优化经典和量子范式中兼容相关性的集合（放松）。该库的设计为模块化，并具有可用使用的能力，同时可以轻松访问低级对象进行自定义修改。
We introduce Inflation, a Python library for assessing whether an observed probability distribution is compatible with a causal explanation. This is a central problem in both theoretical and applied sciences, which has recently witnessed significant advances from the area of quantum nonlocality, namely, in the development of inflation techniques. Inflation is an extensible toolkit that is capable of solving pure causal compatibility problems and optimization over (relaxations of) sets of compatible correlations in both the classical and quantum paradigms. The library is designed to be modular and with the ability of being ready-to-use, while keeping an easy access to low-level objects for custom modifications.
