论文标题
一般概率理论中的集合和转向
Assemblages and steering in general probabilistic theories
论文作者
论文摘要
我们研究了一般概率理论框架的转向。我们表明，对于二分法组合，可以通过某种张量交叉标准来表征转向的特征，这也与转向鲁棒性给出的转向学位有关。另一个贡献是观察到，可以使用Choquet理论方便地处理GPT中的转向，以实现状态空间的概率度量。特别是，我们发现了二分法组合的通用转向度的变异表达，并获得表征与最近发现的量子病例的某些条件相似的不可行动状态的条件。该设置还使我们能够轻松地将结果扩展到具有任意结果的无限维度和任意数量的测量数量。
We study steering in the framework of general probabilistic theories. We show that for dichotomic assemblages, steering can be characterized in terms of a certain tensor cross norm, which is also related to a steering degree given by steering robustness. Another contribution is the observation that steering in GPTs can be conveniently treated using Choquet theory for probability measures on the state space. In particular, we find a variational expression for universal steering degree for dichotomic assemblages and obtain conditions characterizing unsteerable states analogous to some conditions recently found for the quantum case. The setting also enables us to rather easily extend the results to infinite dimensions and arbitrary numbers of measurements with arbitrary outcomes.
