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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 02, 2017
Source ID
10.1098/rsta.2016.0389

Entities

People

  • Ehtibar N Dzhafarov
  • Janne V. Kujala
  • Víctor H. Cervantes

Organizations

  • Air Force Office of Scientific Research
  • Graduate School, Purdue University
  • Purdue University
  • University of Jyväskylä

Tags

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Mathematical Modeling and Probability Theory.