Probabilistic models on contextuality scenarios

TL;DR

This paper introduces a hypergraph-based framework for modeling probabilities in Bell and contextuality experiments, unifying concepts of contextuality and nonlocality, and summarizes related results.

Contribution

It presents a novel hypergraph framework for probabilistic models in contextuality scenarios, unifying contextuality and nonlocality concepts.

Findings

Unifies notions of contextuality and nonlocality

Provides a flexible hypergraph-based modeling approach

Summarizes key results in the field

Abstract

We introduce a framework to describe probabilistic models in Bell experiments, and more generally in contextuality scenarios. Such a scenario is a hypergraph whose vertices represent elementary events and hyperedges correspond to measurements. A probabilistic model on such a scenario associates to each event a probability, in such a way that events in a given measurement have a total probability equal to one. We discuss the advantages of this framework, like the unification of the notions of contexuality and nonlocality, and give a short overview of results obtained elsewhere.