Titel
Machine-learning-based device-independent certification of quantum networks
Autor*in
Nicola D'Alessandro
Dipartimento di Fisica - Sapienza Università di Roma
Autor*in
Beatrice Polacchi
Dipartimento di Fisica - Sapienza Università di Roma
Autor*in
George Moreno
International Institute of Physics, Federal University of Rio Grande do Norte
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Abstract
Witnessing 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.
Stichwort
Quantum Information, Science & Technology
Objekt-Typ
Sprache
Englisch [eng]
Persistent identifier
https://phaidra.univie.ac.at/o:2061963
Erschienen in
Titel
Physical Review Research
Band
5
Ausgabe
2
ISSN
2643-1564
Erscheinungsdatum
2023
Verlag
American Physical Society (APS)
Projektnummer
884676 – European Union (all programmes)
Erscheinungsdatum
2023
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