Constraints on nonlocality in networks from no-signaling and independence

Nicolas Gisin (), Jean-Daniel Bancal (), Yu Cai (), Patrick Remy, Armin Tavakoli, Emmanuel Zambrini Cruzeiro, Sandu Popescu and Nicolas Brunner
Additional contact information
Nicolas Gisin: Université de Genève
Jean-Daniel Bancal: Université de Genève
Yu Cai: Université de Genève
Patrick Remy: Université de Genève
Armin Tavakoli: Université de Genève
Emmanuel Zambrini Cruzeiro: Université de Genève
Sandu Popescu: Tyndall Avenue
Nicolas Brunner: Université de Genève

Nature Communications, 2020, vol. 11, issue 1, 1-6

Abstract: Abstract The possibility of Bell inequality violations in quantum theory had a profound impact on our understanding of the correlations that can be shared by distant parties. Generalizing the concept of Bell nonlocality to networks leads to novel forms of correlations, the characterization of which is, however, challenging. Here, we investigate constraints on correlations in networks under the natural assumptions of no-signaling and independence of the sources. We consider the triangle network with binary outputs, and derive strong constraints on correlations even though the parties receive no input, i.e., each party performs a fixed measurement. We show that some of these constraints are tight, by constructing explicit local models (i.e. where sources distribute classical variables) that can saturate them. However, we also observe that other constraints can apparently not be saturated by local models, which opens the possibility of having nonlocal (but non-signaling) correlations in the triangle network with binary outputs.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-020-16137-4 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-16137-4

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-020-16137-4

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().