Probabilistic Foundations of Contextuality
Ehtibar Dzhafarov, Janne Kujala

TL;DR
This paper develops a probabilistic framework for understanding contextuality in measurements, especially when traditional assumptions like no-disturbance are violated, by introducing a generalized approach based on maximal probability of equality.
Contribution
It reformulates contextuality using the Contextuality-by-Default approach and generalizes the concept of measurement compatibility to systems with disturbance or signaling.
Findings
Applicable to quantum systems with disturbance or signaling
Provides a unified probabilistic framework for contextuality
Illustrated on various binary measurement systems
Abstract
Contextuality is usually defined as absence of a joint distribution for a set of measurements (random variables) with known joint distributions of some of its subsets. However, if these subsets of measurements are not disjoint, contextuality is mathematically impossible even if one generally allows (as one must) for random variables not to be jointly distributed. To avoid contradictions one has to adopt the Contextuality-by-Default approach: measurements made in different contexts are always distinct and stochastically unrelated to each other. Contextuality is reformulated then in terms of the (im)possibility of imposing on all the measurements in a system a joint distribution of a particular kind: such that any measurements of one and the same property made in different contexts satisfy a specified property, . In the traditional analysis of contextuality …
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