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Non-Kochen–Specker Contextuality
Quantum contextuality supports quantum computation and communication. One of its main vehicles is hypergraphs. The most elaborated are the Kochen–Specker ones, but there is also another class of contextual sets that are not of this kind. Their representation has been mostly operator-based and limite...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453090/ https://www.ncbi.nlm.nih.gov/pubmed/37628147 http://dx.doi.org/10.3390/e25081117 |
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author | Pavičić, Mladen |
author_facet | Pavičić, Mladen |
author_sort | Pavičić, Mladen |
collection | PubMed |
description | Quantum contextuality supports quantum computation and communication. One of its main vehicles is hypergraphs. The most elaborated are the Kochen–Specker ones, but there is also another class of contextual sets that are not of this kind. Their representation has been mostly operator-based and limited to special constructs in three- to six-dim spaces, a notable example of which is the Yu-Oh set. Previously, we showed that hypergraphs underlie all of them, and in this paper, we give general methods—whose complexity does not scale up with the dimension—for generating such non-Kochen–Specker hypergraphs in any dimension and give examples in up to 16-dim spaces. Our automated generation is probabilistic and random, but the statistics of accumulated data enable one to filter out sets with the required size and structure. |
format | Online Article Text |
id | pubmed-10453090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104530902023-08-26 Non-Kochen–Specker Contextuality Pavičić, Mladen Entropy (Basel) Article Quantum contextuality supports quantum computation and communication. One of its main vehicles is hypergraphs. The most elaborated are the Kochen–Specker ones, but there is also another class of contextual sets that are not of this kind. Their representation has been mostly operator-based and limited to special constructs in three- to six-dim spaces, a notable example of which is the Yu-Oh set. Previously, we showed that hypergraphs underlie all of them, and in this paper, we give general methods—whose complexity does not scale up with the dimension—for generating such non-Kochen–Specker hypergraphs in any dimension and give examples in up to 16-dim spaces. Our automated generation is probabilistic and random, but the statistics of accumulated data enable one to filter out sets with the required size and structure. MDPI 2023-07-26 /pmc/articles/PMC10453090/ /pubmed/37628147 http://dx.doi.org/10.3390/e25081117 Text en © 2023 by the author. 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 Pavičić, Mladen Non-Kochen–Specker Contextuality |
title | Non-Kochen–Specker Contextuality |
title_full | Non-Kochen–Specker Contextuality |
title_fullStr | Non-Kochen–Specker Contextuality |
title_full_unstemmed | Non-Kochen–Specker Contextuality |
title_short | Non-Kochen–Specker Contextuality |
title_sort | non-kochen–specker contextuality |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10453090/ https://www.ncbi.nlm.nih.gov/pubmed/37628147 http://dx.doi.org/10.3390/e25081117 |
work_keys_str_mv | AT pavicicmladen nonkochenspeckercontextuality |