The Characterization of Noncontextuality in the Framework of Generalized Probabilistic Theories
David Schmid, John Selby, Elie Wolfe, Ravi Kunjwal, Robert W. Spekkens

TL;DR
This paper investigates how classicality can be characterized within generalized probabilistic theories by introducing the concept of simplex-embeddability, linking operational noncontextuality to geometric conditions in GPTs.
Contribution
It introduces the notion of simplex-embeddability as a geometric criterion for classicality in GPTs, extending traditional ideas of state space simplicity.
Findings
Mapping operational theories to GPTs preserves noncontextuality constraints.
Simplex-embeddability is a geometric condition that characterizes classicality in GPTs.
Application to prepare-measure experiments helps identify nonclassical behavior.
Abstract
To make precise the sense in which the operational predictions of quantum theory conflict with a classical worldview, it is necessary to articulate a notion of classicality within an operational framework. A widely applicable notion of classicality of this sort is whether or not the predictions of a given operational theory can be explained by a generalized-noncontextual ontological model. We here explore what notion of classicality this implies for the generalized probabilistic theory (GPT) that arises from a given operational theory, focusing on prepare-measure scenarios. We first show that, when mapping an operational theory to a GPT by quotienting relative to operational equivalences, the constraint of explainability by a generalized-noncontextual ontological model is mapped to the constraint of explainability by an ontological model. We then show that, under the additional…
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