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Genuine Randomness vis-a-vis Nonlocality: Hardy and Hardy type Relations

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 نشر من قبل Urbasi Sinha Prof.
 تاريخ النشر 2020
  مجال البحث فيزياء
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We explore the relationship between randomness and nonlocality based on arguments which demonstrate nonlocality without requiring Bell-type inequalities, such as using Hardy relations and its variant like Cabello-Liang (CL) relations. We first clarify the way these relations enable certification of Genuine Randomness (GR) based on the No-signalling principle. Subsequently, corresponding to a given amount of nonlocality, using the relevant quantifier of GR, we demonstrate the following results: (a) We show that in the 2-2-2 scenario, it is possible to achieve close to the theoretical maximum value of 2 bits amount of GR using CL relations. Importantly, this maximum value is achieved using pure non-maximally entangled states for the measurement settings entailing small amount of nonlocality. Thus, this illustrates quantitative incommensurability between maximum achievable certified randomness, nonlocality and entanglement in the same testable context. (b) We also obtain the device-independent guaranteed amount of GR based on Hardy and CL relations, taking into account the effect of varying preparation procedure which is necessary for ensuring the desired security in this case against adversarial guessing attack. This result is compared with that obtained earlier for the Bell-CHSH case. We find that the monotonicity between such guaranteed randomness and nonlocality persists for the Hardy/CL like for Bell-CHSH inequality, thereby showing commensurability between guaranteed randomness and nonlocality, in contrast to the case of maximum achievable randomness. The results of this combined study of maximum achievable as well as guaranteed amounts of GR, obtained for both fixed and varying preparation procedures, demonstrate that the nature of quantitative relationship between randomness and nonlocality is crucially dependent on which aspect (guaranteed/maximum amount) of GR is considered.



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