Instituto Internacional de Física
URI Permanente desta comunidadehttps://repositorio.ufrn.br/handle/123456789/30127
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Navegando Instituto Internacional de Física por Autor "Agresti, Iris"
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Artigo Experimental test of quantum causal influences(Sciance Advances, 2022-02-25) Agresti, Iris; Poderini, Davide; Polacchi, Beatrice; Miklin, Nikolai; Gachechiladze, Mariami; Suprano, Alessia; Polino, Emanuele; Milani, Giorgio; Carvacho, Gonzalo; Araújo, Rafael Chaves Souto; Sciarrino, FabioSince Bell’s theorem, it is known that local realism fails to explain quantum phenomena. Bell inequality violations manifestly show the incompatibility of quantum theory with classical notions of cause and effect. As recently found, however, the instrumental scenario—a pivotal tool in causal inference—allows for nonclassicality signatures going beyond this paradigm. If we are not limited to observational data and can intervene in our setup, then we can witness quantum violations of classical bounds on the causal influence among the involved variables even when no Bell-like violation is possible. That is, through interventions, the quantum behavior of a system that would seem classical can be demonstrated. Using a photonic setup—faithfully implementing the instrumental causal structure and switching between observation and intervention run by run—we experimentally witness such a nonclassicality. We also test quantum bounds for the causal influence, showing that they provide a reliable tool for quantum causal modelingArtigo Machine-learning-based device-independent certification of quantum networks(Physical Review Research, 2023-04-10) D’Alessandro, Nicola; Polacch, Beatrice; Moreno Filho, Marcos George Magalhães; Polino, Emanuele; Araújo, Rafael Chaves Souto; Agresti, Iris; Sciarrino, FabioWitnessing nonclassical behavior is a crucial ingredient in quantum information processing. For that, one has to optimize the quantum features a given physical setup can give rise to, which is a hard computational task currently tackled with semidefinite programming, a method limited to linear objective functions and that becomes prohibitive as the complexity of the system grows. Here, we propose an alternative strategy, which exploits a feedforward artificial neural network to optimize the correlations compatible with arbitrary quantum networks. A remarkable step forward with respect to existing methods is that it deals with nonlinear optimization constraints and objective functions, being applicable to scenarios featuring independent sources and nonlinear entanglement witnesses. Furthermore, it offers a significant speedup in comparison with other approaches, thus allowing to explore previously inaccessible regimes. We also extend the use of the neural network to the experimental realm, a situation in which the statistics are unavoidably affected by imperfections, retrieving device-independent uncertainty estimates on Bell-like violations obtained with independent sources of entangled photon states. In this way, this work paves the way for the certification of quantum resources in networks of growing size and complexity