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Experimental violation of n-locality in a star quantum network

Physics

Experimental violation of n-locality in a star quantum network

D. Poderini, I. Agresti, et al.

This groundbreaking research reveals an experiment that defies conventional boundaries by demonstrating nonlocal correlations in star-shaped quantum networks. Conducted by a team including Davide Poderini and Iris Agresti, the findings promise new horizons for quantum information processing applications where the interplay of source independence and entanglement challenges classical models.

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~3 min • Beginner • English
Abstract
The launch of a satellite capable of distributing entanglement through long distances and the first loophole-free violation of Bell inequalities are milestones indicating a clear path for the establishment of quantum networks. However, nonlocality in networks with independent entanglement sources has only been experimentally verified in simple tripartite networks, via the violation of bilocality inequalities. Here, by using a scalable photonic platform, we implement star-shaped quantum networks consisting of up to five distant nodes and four independent entanglement sources. We exploit this platform to violate the chained n-locality inequality and thus witness, in a device-independent way, the emergence of nonlocal correlations among the nodes of the implemented networks. These results open new perspectives for quantum information processing applications in the relevant regime where the observed correlations are compatible with standard local hidden variable models but are non-classical if the independence of the sources is taken into account.
Publisher
Nature Communications
Published On
May 18, 2020
Authors
Davide Poderini, Iris Agresti, Guglielmo Marchese, Emanuele Polino, Taira Giordani, Alessia Suprano, Mauro Valeri, Giorgio Milani, Nicolò Spagnolo, Gonzalo Carvacho, Rafael Chaves, Fabio Sciarrino
Tags
quantum networks
entanglement
nonlocal correlations
photonic platform
device-independent
quantum information processing
local hidden variable models
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