scholarly journals Reference-Frame-Independent Design of Phase-Matching Quantum Key Distribution

2021 ◽  
Vol 16 (3) ◽  
Author(s):  
Anran Jin ◽  
Pei Zeng ◽  
Richard V. Penty ◽  
Xiongfeng Ma
Keyword(s):  
Reference Frame ◽  
Quantum Key Distribution ◽  
Key Distribution ◽  
Phase Matching ◽  
Independent Design

Phase-matching quantum key distribution with light source monitoring

2021 ◽  
Author(s):  
Wen-Ting Li ◽  
Le Wang ◽  
Wei Li ◽  
Sheng-Mei Zhao
Keyword(s):  
Light Source ◽  
Quantum Key Distribution ◽  
Source Monitoring ◽  
Transmission Loss ◽  
Key Distribution ◽  
Phase Matching ◽  
Measurement Device ◽  
Source Condition ◽  
Source Fluctuation ◽  
The Ideal

Abstract The transmission loss of photons during quantum key distribution(QKD) process leads to the linear key rate bound for practical QKD systems without quantum repeaters. Phase matching quantum key distribution (PM-QKD) protocol, an novel QKD protocol, can overcome the constraint with a measurement-device-independent structure, while it still requires the light source to be ideal. This assumption is not guaranteed in practice, leading to practical secure issues. In this paper, we propose a modified PM-QKD protocol with a light source monitoring, named PM-QKD-LSM protocol, which can guarantee the security of the system under the non-ideal source condition. The results show that our proposed protocol performs almost the same as the ideal PM-QKD protocol even considering the imperfect factors in practical systems. PM-QKD-LSM protocol has a better performance with source fluctuation, and it is robust in symmetric or asymmetric cases.

scholarly journals Machine Learning-Assisted Measurement Device-Independent Quantum Key Distribution on Reference Frame Calibration

Entropy ◽  
2021 ◽  
Vol 23 (10) ◽  
pp. 1242
Author(s):  
Sihao Zhang ◽  
Jingyang Liu ◽  
Guigen Zeng ◽  
Chunhui Zhang ◽  
Xingyu Zhou ◽  
...  
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Reference Frame ◽  
Quantum Key Distribution ◽  
Short Term Memory ◽  
Key Distribution ◽  
Transmission Efficiency ◽  
System Stability ◽  
Measurement Device ◽  
Measurement Device Independent

In most of the realistic measurement device-independent quantum key distribution (MDI-QKD) systems, efficient, real-time feedback controls are required to maintain system stability when facing disturbance from either external environment or imperfect internal components. Traditionally, people either use a “scanning-and-transmitting” program or insert an extra device to make a phase reference frame calibration for a stable high-visibility interference, resulting in higher system complexity and lower transmission efficiency. In this work, we build a machine learning-assisted MDI-QKD system, where a machine learning model—the long short-term memory (LSTM) network—is for the first time to apply onto the MDI-QKD system for reference frame calibrations. In this machine learning-assisted MDI-QKD system, one can predict out the phase drift between the two users in advance, and actively perform real-time phase compensations, dramatically increasing the key transmission efficiency. Furthermore, we carry out corresponding experimental demonstration over 100 km and 250 km commercial standard single-mode fibers, verifying the effectiveness of the approach.

scholarly journals Reference-frame-independent quantum key distribution

2010 ◽  
Vol 82 (1) ◽  
Author(s):  
Anthony Laing ◽  
Valerio Scarani ◽  
John G. Rarity ◽  
Jeremy L. O’Brien
Keyword(s):  
Reference Frame ◽  
Quantum Key Distribution ◽  
Key Distribution

Reference-frame-independent quantum key distribution with an untrusted source

2020 ◽  
Vol 29 (3) ◽  
pp. 030303
Author(s):  
Jia-Ji Li ◽  
Yang Wang ◽  
Hong-Wei Li ◽  
Wan-Su Bao
Keyword(s):  
Reference Frame ◽  
Quantum Key Distribution ◽  
Key Distribution
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