Discrete-modulated continuous-variable quantum key distribution with a machine-learning-based detector

2018 ◽  
Vol 57 (06) ◽  
pp. 1 ◽  
Author(s):  
Jiawei Li ◽  
Ying Guo ◽  
Xudong Wang ◽  
Cailang Xie ◽  
Ling Zhang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Quantum Key Distribution ◽  
Key Distribution ◽  
Continuous Variable

scholarly journals Secure Continuous-Variable Quantum Key Distribution with Machine Learning

Photonics ◽  
2021 ◽  
Vol 8 (11) ◽  
pp. 511
Author(s):  
Duan Huang ◽  
Susu Liu ◽  
Ling Zhang
Keyword(s):  
Machine Learning ◽  
Quantum Key Distribution ◽  
Key Distribution ◽  
Continuous Variable ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
The Common ◽  
Practical Security

Quantum key distribution (QKD) offers information-theoretical security, while real systems are thought not to promise practical security effectively. In the practical continuous-variable (CV) QKD system, the deviations between realistic devices and idealized models might introduce vulnerabilities for eavesdroppers and stressors for two parties. However, the common quantum hacking strategies and countermeasures inevitably increase the complexity of practical CV systems. Machine-learning techniques are utilized to explore how to perceive practical imperfections. Here, we review recent works on secure CVQKD systems with machine learning, where the methods for detections and attacks were studied.

scholarly journals Machine learning aided carrier recovery in continuous-variable quantum key distribution

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Hou-Man Chin ◽  
Nitin Jain ◽  
Darko Zibar ◽  
Ulrik L. Andersen ◽  
Tobias Gehring
Keyword(s):  
Machine Learning ◽  
Phase Noise ◽  
Quantum Key Distribution ◽  
Unscented Kalman Filter ◽  
Key Distribution ◽  
Continuous Variable ◽  
Excess Noise ◽  
Carrier Recovery ◽  
Pilot Signal ◽  
Wide Range

AbstractThe secret key rate of a continuous-variable quantum key distribution (CV-QKD) system is limited by excess noise. A key issue typical to all modern CV-QKD systems implemented with a reference or pilot signal and an independent local oscillator is controlling the excess noise generated from the frequency and phase noise accrued by the transmitter and receiver. Therefore accurate phase estimation and compensation, so-called carrier recovery, is a critical subsystem of CV-QKD. Here, we explore the implementation of a machine learning framework based on Bayesian inference, namely an unscented Kalman filter (UKF), for estimation of phase noise and compare it to a standard reference method and a previously demonstrated machine learning method. Experimental results obtained over a 20-km fibre-optic link indicate that the UKF can ensure very low excess noise even at low pilot powers. The measurements exhibited low variance and high stability in excess noise over a wide range of pilot signal to noise ratios. This may enable CV-QKD systems with low hardware implementation complexity which can seamlessly work on diverse transmission lines.

scholarly journals An FPGA-Based LDPC Decoder With Ultra-Long Codes for Continuous-Variable Quantum Key Distribution

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 47687-47697
Author(s):  
Shen-Shen Yang ◽  
Jian-Qiang Liu ◽  
Zhen-Guo Lu ◽  
Zeng-Liang Bai ◽  
Xu-Yang Wang ◽  
...  
Keyword(s):  
Quantum Key Distribution ◽  
Key Distribution ◽  
Continuous Variable ◽  
Ldpc Decoder

scholarly journals A novel error correction protocol for continuous variable quantum key distribution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kadir Gümüş ◽  
Tobias A. Eriksson ◽  
Masahiro Takeoka ◽  
Mikio Fujiwara ◽  
Masahide Sasaki ◽  
...  
Keyword(s):  
Error Correction ◽  
Quantum Key Distribution ◽  
Ldpc Codes ◽  
Key Distribution ◽  
Continuous Variable ◽  
Early Termination ◽  
Parity Check ◽  
Secret Key ◽  
Ldpc Decoder ◽  
And Performance

AbstractReconciliation is a key element of continuous-variable quantum key distribution (CV-QKD) protocols, affecting both the complexity and performance of the entire system. During the reconciliation protocol, error correction is typically performed using low-density parity-check (LDPC) codes with a single decoding attempt. In this paper, we propose a modification to a conventional reconciliation protocol used in four-state protocol CV-QKD systems called the multiple decoding attempts (MDA) protocol. MDA uses multiple decoding attempts with LDPC codes, each attempt having fewer decoding iteration than the conventional protocol. Between each decoding attempt we propose to reveal information bits, which effectively lowers the code rate. MDA is shown to outperform the conventional protocol in regards to the secret key rate (SKR). A 10% decrease in frame error rate and an 8.5% increase in SKR are reported in this paper. A simple early termination for the LDPC decoder is also proposed and implemented. With early termination, MDA has decoding complexity similar to the conventional protocol while having an improved SKR.

Sign in / Sign up

Export Citation Format

Share Document