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We derive a sufficient condition for advantage distillation to be secure against collective attacks in device-independent quantum key distribution (DIQKD), focusing on the repetition-code protocol. In addition, we describe a semidefinite programming method to check whether this condition holds for any probability distribution obtained in a DIQKD protocol. Applying our method to various probability distributions, we find that advantage distillation is possible up to depolarising-noise values of $q approx 9.1%$ or limited detector efficiencies of $eta approx 89.1%$ in a 2-input 2-output scenario. This exceeds the noise thresholds of $q approx 7.1%$ and $eta approx 90.7%$ respectively for DIQKD with one-way error correction using the CHSH inequality, thereby showing that it is possible to distill secret key beyond those thresholds.
It is known that advantage distillation (that is, information reconciliation using two-way communication) improves noise tolerances for quantum key distribution (QKD) setups. Two-way communication is hence also of interest in the device-independent c
Device-independent quantum key distribution (DIQKD) is the art of using untrusted devices to distribute secret keys in an insecure network. It thus represents the ultimate form of cryptography, offering not only information-theoretic security against
Untrusted node networks initially implemented by measurement-device-independent quantum key distribution (MDI-QKD) protocol are a crucial step on the roadmap of the quantum Internet. Considering extensive QKD implementations of trusted node networks,
Measurement-device-independent quantum key distribution (MDIQKD) is a revolutionary protocol since it is physically immune to all attacks on the detection side. However, the protocol still keeps the strict assumptions on the source side that the four
Quantum key distribution (QKD) promises security stemming from the laws of quantum physics. QKD devices based on integrated chips not only provides miniaturization, but also enhanced performance, which is important to practical and scalable networks.