Explaining quantum correlations through evolution of causal models

Harper, R; Chapman, RJ; Ferrie, C; Granade, C; Kueng, R; Naoumenko, D; Flammia, ST; Peruzzo, A

Explaining quantum correlations through evolution of causal models

Harper, R Chapman, RJ Ferrie, C

Granade, C Kueng, R Naoumenko, D Flammia, ST Peruzzo, A

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Publication Type:: Journal Article
Citation:: Physical Review A, 2017, 95 (4)
Issue Date:: 2017-04-17

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Field	Value	Language
dc.contributor.author	Harper, R	en_US
dc.contributor.author	Chapman, RJ	en_US
dc.contributor.author	Ferrie, C https://orcid.org/0000-0003-2736-9943	en_US
dc.contributor.author	Granade, C	en_US
dc.contributor.author	Kueng, R	en_US
dc.contributor.author	Naoumenko, D	en_US
dc.contributor.author	Flammia, ST	en_US
dc.contributor.author	Peruzzo, A	en_US
dc.date.issued	2017-04-17	en_US
dc.identifier.citation	Physical Review A, 2017, 95 (4)	en_US
dc.identifier.issn	2469-9926	en_US
dc.identifier.uri	http://hdl.handle.net/10453/124676
dc.description.abstract	© 2017 American Physical Society. We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.	en_US
dc.relation.ispartof	Physical Review A	en_US
dc.relation.isbasedon	10.1103/PhysRevA.95.042120	en_US
dc.subject.classification	General Physics	en_US
dc.title	Explaining quantum correlations through evolution of causal models	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	95	en_US
utslib.for	0203 Classical Physics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	02 Physical Sciences	en_US
utslib.for	03 Chemical Sciences	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - QSI - Centre for Quantum Software and Information
utslib.copyright.status	open_access
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	95	en_US

Abstract:

© 2017 American Physical Society. We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.

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http://hdl.handle.net/10453/124676