Please use this identifier to cite or link to this item: http://hdl.handle.net/2289/8055
Title: Testing of quantum nonlocal correlations under constrained free will and imperfect detectors
Authors: Sadhu, Abhishek
Das, Siddhartha
Keywords: nonlocality
photonics
quantum correlations in quantum information
cryptography
quantum entaglement
quantum information theory
Issue Date: 17-Jan-2023
Publisher: American Physical Society
Citation: Physical Review A, 2023, Vol.107, p012212
Abstract: In this work, we deal with the relaxation of two central assumptions in standard locally realistic hidden variable (LRHV) inequalities: free will in choosing measurement settings, and the presence of perfect detectors at the measurement devices. Quantum correlations violating LRHV inequalities are called quantum nonlocal correlations. In principle, in an adversarial situation, there could be a hidden variable introducing bias in the selection of measurement settings, but observers with no access to that hidden variable could be unaware of the bias. In practice, however, detectors do not have perfect efficiency. A main focus of this paper is the introduction of the framework in which given a quantum state with nonlocal behavior under constrained free will, we can determine the threshold values of detector parameters (detector inefficiency and dark counts) such that the detectors are robust enough to certify nonlocality. We also introduce a class of LRHV inequalities with constrained free will, and we discuss their implications in the testing of quantum nonlocal correlations.
Description: Restricted Access. An open-access version is available at arXiv.org (one of the alternative locations)
URI: http://hdl.handle.net/2289/8055
ISSN: 1050-2947
1094-1622 (Online)
Alternative Location: https://arxiv.org/abs/2209.05444
https://ui.adsabs.harvard.edu/abs/2023PhRvA.107a2212S/abstract
https://inspirehep.net/literature/2150705
https://doi.org/10.1103/PhysRevA.107.012212
Copyright: 2023 American Physical Society
Appears in Collections:Research Papers (LAMP)

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