Versatile security analysis of measurement-device-independent quantum key distribution

Abstract

Measurement-device-independent quantum key distribution (MDI-QKD) is the only known QKD scheme that can completely overcome the problem of detection side-channel attacks. Yet, despite its practical importance, there is no standard approach towards proving the security of MDI-QKD. Here, we present a simple numerical method that can efficiently compute almost-tight security bounds for any discretely modulated MDI-QKD protocol. To demonstrate the broad utility of our method, we use it to analyze the security of coherent-state MDI-QKD, decoy-state MDI-QKD with leaky sources, and a variant of twin-field QKD called phase-matching QKD. In all of the numerical simulations (using realistic detection models) we find that our method gives significantly higher secret key rates than those obtained with current security proof techniques. Interestingly, we also find that phase-matching QKD using only two coherent test states is enough to overcome the fundamental rate-distance limit of QKD. Taken together, these findings suggest that our security proof method enables a versatile, fast, and possibly optimal approach towards the security validation of practical MDI-QKD systems.

Optimized protocol for twin-field quantum key distribution

“…During the preparation of this paper, we found that Primaatmaja et al 30 proposed an open question that if coding phases in TF-QKD under different bases, which is quite similar to our idea of phase discrete randomization, can improve secret key rate significantly. Their open question is answered by our finding that M = 2 is almost optimal in some sense.…”

Numerical finite-key analysis of quantum key distribution

“…The numerical method presented in refs. 10,11 has been shown to be compatible with decoy states-obviating the use of squashing maps-by breaking the infinite-dimensional problem into the dimensions of the signals. This warrants a further study that combines this method with our approach of handling the finite-size statistics.…”

“…Therefore, we have ε 0 ¼ ε sec =11 for the calculation with von Neumann entropy (Eq. (11) with SDPs (35) and (36)) and ε 0 ¼ ε sec =10 for the calculation with min-entropy (Eq. (14) with SDP (45)).…”

“…Commercially available convex optimization tools, such as Mosek 7 , SeDuMi 8 , or SDPT3 9 , can therefore be used to reliably solve the problem. A more recent technique opted to compute the secret key rate by directly bounding the quantum error rate of a protocol using the Gram matrix of the eavesdropper's information 10,11 . Nevertheless, the problems formulated so far still assumed that Alice and Bob have exchanged an infinite number of signals (and an infinite-key length), which is practically impossible.…”

Twin-Field Quantum Key Distribution with Fully Discrete Phase Randomization

“…In particular, inspired by the work of Ref. [24], we use semidefinite programming (SDP) techniques to estimate the phase-error rate. We note that, in Ref.…”