Continuous-Variable Quantum Key Distribution with a Real Local Oscillator and without Auxiliary Signals

TL;DR

This paper demonstrates, for the first time, that continuous-variable quantum key distribution can be performed with a real local oscillator and without auxiliary signals by using machine learning, achieving high key rates over fiber.

Contribution

It introduces a novel CV-QKD implementation using a real local oscillator without auxiliary signals, enabled by machine learning, simplifying the system for practical deployment.

Findings

Operates down to -19.1 dB SNR in experimental setup.

Achieves a key rate of 9.2 Mbit/s over 26 km fiber.

First experimental demonstration of this approach.

Abstract

Continuous-variable quantum key distribution (CV-QKD) is realized with coherent detection and is therefore very suitable for a cost-efficient implementation. The major challenge in CV-QKD is mitigation of laser phase noise at a signal to noise ratio of much less than 0 dB. So far, this has been achieved with a remote local oscillator or with auxiliary signals. For the first time, we experimentally demonstrate that CV-QKD can be performed with a real local oscillator and without auxiliary signals which is achieved by applying Machine Learning methods. It is shown that, with the most established discrete modulation protocol, the experimental system works down to a quantum channel signal to noise ratio of -19.1 dB. The performance of the experimental system allows CV-QKD at a key rate of 9.2 Mbit/s over a fiber distance of 26 km. After remote local oscillator and auxiliary signal aided CV-QKD, this could mark a starting point for a third generation of CV-QKD systems that are even more attractive for a wide implementation because they are almost identical to standard coherent systems.