Unknown

Dataset Information

0

Contextuality in canonical systems of random variables.


ABSTRACT: Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal coupling (the joint distribution imposed on them so that they coincide with maximal possible probability). The system is contextual if these maximal couplings are incompatible with the joint distributions of the context-sharing random variables. We propose to represent any system of measurements in a canonical form and to consider the system contextual if and only if its canonical representation is contextual. As an illustration, we establish a criterion for contextuality of the canonical system consisting of all dichotomizations of a single pair of content-sharing categorical random variables.This article is part of the themed issue 'Second quantum revolution: foundational questions'.

SUBMITTER: Dzhafarov EN 

PROVIDER: S-EPMC5628257 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

altmetric image

Publications

Contextuality in canonical systems of random variables.

Dzhafarov Ehtibar N EN   Cervantes Víctor H VH   Kujala Janne V JV  

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences 20171101 2106


Random variables representing measurements, broadly understood to include any responses to any inputs, form a system in which each of them is uniquely identified by its content (that which it measures) and its context (the conditions under which it is recorded). Two random variables are jointly distributed if and only if they share a context. In a canonical representation of a system, all random variables are binary, and every content-sharing pair of random variables has a unique maximal couplin  ...[more]

Similar Datasets

| S-EPMC4070742 | biostudies-other
| S-EPMC3142115 | biostudies-literature
| S-EPMC8193767 | biostudies-literature
| S-EPMC6754711 | biostudies-literature
| S-EPMC5193442 | biostudies-literature
| S-EPMC6879595 | biostudies-literature
| S-EPMC8177743 | biostudies-literature
| S-EPMC5059491 | biostudies-literature
| S-EPMC5065255 | biostudies-literature
| S-EPMC6761946 | biostudies-literature