经验模型的类别

CoRR Pub Date : 2018-04-04 DOI:10.4204/EPTCS.287.14
M. Karvonen
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引用次数: 14

摘要

提出了一种适合于上下文理论方法的态射概念,从而形成了上下文的资源理论。关键特征包括在测量场景之间使用潜在关系而不是函数,并允许结果到结果的随机映射。这形式化了一种直观的想法,即在预共享的经典随机性的帮助下,使用一个经验模型来模拟另一个模型。这允许人们根据态射重新解释概念和早期的结果。最值得注意的是:非上下文模型正是那些允许终端对象的态射的模型;语境分数是泛函的;graham -约简引出态射,重新诠释Vorob'evs定理;不能克隆上下文模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Categories of empirical models
A notion of morphism that is suitable for the sheaf-theoretic approach to contextuality is developed, resulting in a resource theory for contextuality. The key features involve using an underlying relation rather than a function between measurement scenarios, and allowing for stochastic mappings of outcomes to outcomes. This formalizes an intuitive idea of using one empirical model to simulate another one with the help of pre-shared classical randomness. This allows one to reinterpret concepts and earlier results in terms of morphisms. Most notably: non-contextual models are precisely those allowing a morphism from the terminal object; contextual fraction is functorial; Graham-reductions induce morphisms, reinterpreting Vorob'evs theorem; contextual models cannot be cloned.
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