Experimental measurement-device-independent quantum key distribution with uncharacterized encoding

Boosting the performance of loss-tolerant measurement-device-independent quantum key distribution

Measurement-device-independent quantum key distribution can remove all possible detector side channels, and is robust against state preparation flaws when further combined with the loss-tolerant method. However, the secure key rate in this scenario is relatively low, thus hindering its practical application. Here, we first present a four-intensity decoy-state protocol where the signal intensity is modulated only in Z basis for key generation while the decoy intensities are modulated in both Z and X bases for parameter estimation. Moreover, we adopt collective constraint and joint-study strategy in statistical fluctuation analysis. We have also experimentally demonstrated this protocol and the result indicates high performance and good security for practical applications.

Experimental three-state measurement-device-independent quantum key distribution with uncharacterized sources

Measurement-device-independent quantum key distribution (MDI-QKD) removes all detector side-channel attacks and guarantees a promising way for remote secret keys sharing. Several proof-of-principal experiments have been demonstrated to show its security and practicality. However, these practical implementations demand mostly, for example, perfect state preparation or completely characterized sources to ensure security, which are difficult to realize with prior art. Here, we investigate a three-state MDI-QKD using uncharacterized sources, with the simple requirement that the encoding state is bidimensional, which eliminates security threats from both the source flaws and detection loopholes. As a demonstration, a proof-of-principal experiment over 170 km transmission distance based on Faraday-Michelson interferometers is achieved, representing, to the best of our knowledge, the longest transmission distance recorded under the same security level.

Experimental quantum key distribution with uncharacterized sources and projective measurements

In theory, quantum key distribution (QKD) can offer information-theoretic secure communication based on the laws of quantum mechanics. However, the vast majority of practical QKD implementations assume the perfect state preparation to ensure security, which is a demanding requirement with current technology. Here, by incorporating the mismatched-basis data, we report an experimental decoy-state QKD demonstration with uncharacterized encoding sources, which only requires that the encoding states are two-dimensional. Furthermore, the measurement operation of the receiver is loosened to be projective measurements. With a rigorous statistical fluctuation analysis, we can distribute secret keys when the transmission distances of the standard fiber link are 101 and 202 km. Our experimental demonstration represents a significant step toward realizing long-distance quantum communication, even with uncharacterized sources and projective measurements.

Improved statistical fluctuation analysis for measurement-device-independent quantum key distribution with four-intensity decoy-state method

Recently Zhang et al [ Phys. Rev. A95, 012333 (2017)] developed a new approach to estimate the failure probability for the decoy-state BB84 QKD system when taking finite-size key effect into account, which offers security comparable to Chernoff bound, while results in an improved key rate and transmission distance. Based on Zhang et al's work, now we extend this approach to the case of the measurement-device-independent quantum key distribution (MDI-QKD), and for the first time implement it onto the four-intensity decoy-state MDI-QKD system. Moreover, through utilizing joint constraints and collective error-estimation techniques, we can obviously increase the performance of practical MDI-QKD systems compared with either three- or four-intensity decoy-state MDI-QKD using Chernoff bound analysis, and achieve much higher level security compared with those applying Gaussian approximation analysis.