Non-locality in theories without the no-restriction hypothesis

The framework of generalized probabilistic theories (GPT) is a widely-used approach for studying the physical foundations of quantum theory. The standard GPT framework assumes the no-restriction hypothesis, in which the state space of a physical theory determines the set of measurements. However,...

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Main Authors: Peter Janotta, Raymond Lal
Format: Article
Language:English
Published: Open Publishing Association 2014-12-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1412.8524v1
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spelling doaj-173971c6557b4a049f4c227d8c75c4052020-11-24T23:18:29ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802014-12-01171Proc. QPL 2013848910.4204/EPTCS.171.8:janottaNon-locality in theories without the no-restriction hypothesisPeter Janotta0Raymond Lal1 Universitaet Wuerzburg University of Oxford The framework of generalized probabilistic theories (GPT) is a widely-used approach for studying the physical foundations of quantum theory. The standard GPT framework assumes the no-restriction hypothesis, in which the state space of a physical theory determines the set of measurements. However, this assumption is not physically motivated. In Janotta and Lal [Phys. Rev. A 87, 052131 (2013)], it was shown how this assumption can be relaxed, and how such an approach can be used to describe new classes of probabilistic theories. This involves introducing a new, more general, definition of maximal joint state spaces, which we call the generalised maximal tensor product. Here we show that the generalised maximal tensor product recovers the standard maximal tensor product when at least one of the systems in a bipartite scenario obeys the no-restriction hypothesis. We also show that, under certain conditions, relaxing the no-restriction hypothesis for a given state space does not allow for stronger non-locality, although the generalized maximal tensor product may allow new joint states.http://arxiv.org/pdf/1412.8524v1
collection DOAJ
language English
format Article
sources DOAJ
author Peter Janotta
Raymond Lal
spellingShingle Peter Janotta
Raymond Lal
Non-locality in theories without the no-restriction hypothesis
Electronic Proceedings in Theoretical Computer Science
author_facet Peter Janotta
Raymond Lal
author_sort Peter Janotta
title Non-locality in theories without the no-restriction hypothesis
title_short Non-locality in theories without the no-restriction hypothesis
title_full Non-locality in theories without the no-restriction hypothesis
title_fullStr Non-locality in theories without the no-restriction hypothesis
title_full_unstemmed Non-locality in theories without the no-restriction hypothesis
title_sort non-locality in theories without the no-restriction hypothesis
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2014-12-01
description The framework of generalized probabilistic theories (GPT) is a widely-used approach for studying the physical foundations of quantum theory. The standard GPT framework assumes the no-restriction hypothesis, in which the state space of a physical theory determines the set of measurements. However, this assumption is not physically motivated. In Janotta and Lal [Phys. Rev. A 87, 052131 (2013)], it was shown how this assumption can be relaxed, and how such an approach can be used to describe new classes of probabilistic theories. This involves introducing a new, more general, definition of maximal joint state spaces, which we call the generalised maximal tensor product. Here we show that the generalised maximal tensor product recovers the standard maximal tensor product when at least one of the systems in a bipartite scenario obeys the no-restriction hypothesis. We also show that, under certain conditions, relaxing the no-restriction hypothesis for a given state space does not allow for stronger non-locality, although the generalized maximal tensor product may allow new joint states.
url http://arxiv.org/pdf/1412.8524v1
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