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Contextuality and Informational Redundancy

A noncontextual system of random variables may become contextual if one adds to it a set of new variables, even if each of them is obtained by the same context-wise function of the old variables. This fact follows from the definition of contextuality, and its demonstration is trivial for inconsisten...

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Autores principales: Dzhafarov, Ehtibar N., Kujala, Janne V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857975/
https://www.ncbi.nlm.nih.gov/pubmed/36673147
http://dx.doi.org/10.3390/e25010006
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author Dzhafarov, Ehtibar N.
Kujala, Janne V.
author_facet Dzhafarov, Ehtibar N.
Kujala, Janne V.
author_sort Dzhafarov, Ehtibar N.
collection PubMed
description A noncontextual system of random variables may become contextual if one adds to it a set of new variables, even if each of them is obtained by the same context-wise function of the old variables. This fact follows from the definition of contextuality, and its demonstration is trivial for inconsistently connected systems (i.e., systems with disturbance). However, it also holds for consistently connected (and even strongly consistently connected) systems, provided one acknowledges that if a given property was not measured in a given context, this information can be used in defining functions among the random variables. Moreover, every inconsistently connected system can be presented as a (strongly) consistently connected system with essentially the same contextuality characteristics.
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spelling pubmed-98579752023-01-21 Contextuality and Informational Redundancy Dzhafarov, Ehtibar N. Kujala, Janne V. Entropy (Basel) Article A noncontextual system of random variables may become contextual if one adds to it a set of new variables, even if each of them is obtained by the same context-wise function of the old variables. This fact follows from the definition of contextuality, and its demonstration is trivial for inconsistently connected systems (i.e., systems with disturbance). However, it also holds for consistently connected (and even strongly consistently connected) systems, provided one acknowledges that if a given property was not measured in a given context, this information can be used in defining functions among the random variables. Moreover, every inconsistently connected system can be presented as a (strongly) consistently connected system with essentially the same contextuality characteristics. MDPI 2022-12-21 /pmc/articles/PMC9857975/ /pubmed/36673147 http://dx.doi.org/10.3390/e25010006 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Dzhafarov, Ehtibar N.
Kujala, Janne V.
Contextuality and Informational Redundancy
title Contextuality and Informational Redundancy
title_full Contextuality and Informational Redundancy
title_fullStr Contextuality and Informational Redundancy
title_full_unstemmed Contextuality and Informational Redundancy
title_short Contextuality and Informational Redundancy
title_sort contextuality and informational redundancy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9857975/
https://www.ncbi.nlm.nih.gov/pubmed/36673147
http://dx.doi.org/10.3390/e25010006
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