Machine learning nonlocal correlations

Silva, Askery Alexandre Canabarro Barbosa da; Brito, Samuraí Gomes de Aguiar; Araújo, Rafael Chaves Souto

Machine learning nonlocal correlations

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dc.contributor.author	Silva, Askery Alexandre Canabarro Barbosa da
dc.contributor.author	Brito, Samuraí Gomes de Aguiar
dc.contributor.author	Araújo, Rafael Chaves Souto
dc.date.accessioned	2020-09-20T18:59:37Z
dc.date.available	2020-09-20T18:59:37Z
dc.date.issued	2019-05-22
dc.description.resumo	The ability to witness nonlocal correlations lies at the core of foundational aspects of quantum mechanics and its application in the processing of information. Commonly, this is achieved via the violation of Bell inequalities. Unfortunately, however, their systematic derivation quickly becomes unfeasible as the scenario of interest grows in complexity. To cope with that, here, we propose a machine learning approach for the detection and quantification of nonlocality. It consists of an ensemble of multilayer perceptrons blended with genetic algorithms achieving a high performance in a number of relevant Bell scenarios. As we show, not only can the machine learn to quantify nonlocality, but discover new kinds of nonlocal correlations inaccessible with other current methods as well. We also apply our framework to distinguish between classical, quantum, and even postquantum correlations. Our results offer a novel method and a proof-of-principle for the relevance of machine learning for understanding nonlocality	pt_BR
dc.identifier.citation	CANABARRO, Askery; BRITO, Samuraí; CHAVES, Rafael. Machine Learning Nonlocal Correlations. Physical Review Letters, [s.l.], v. 122, n. 20, p. 200401, 22 maio 2019. Disponível em: https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.122.200401. Acesso em: 03 set. 2020. http://dx.doi.org/10.1103/physrevlett.122.200401.	pt_BR
dc.identifier.doi	10.1103/physrevlett.122.200401.
dc.identifier.issn	0031-9007
dc.identifier.issn	1079-7114
dc.identifier.uri	https://repositorio.ufrn.br/jspui/handle/123456789/30124
dc.language	en	pt_BR
dc.publisher	American Physical Society	pt_BR
dc.subject	Quantum mechanics	pt_BR
dc.title	Machine learning nonlocal correlations	pt_BR
dc.type	article	pt_BR