Machine learning based joint polarization and phase compensation for CV-QKD-Reference-Cited by-同舟云学术

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Machine learning based joint polarization and phase compensation for CV-QKD

Published:2023 Issue: Volume: Page:
ISSN:
Container-title:Optical Fiber Communication Conference (OFC) 2023
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Author:

Chin Hou-Man,Hajomer Adnan A.E.,Jain Nitin,Andersen Ulrik L.,Gehring Tobias

Abstract

We investigated a machine learning method for joint estimation of polarization and phase for use in a Gaussian modulated CV-QKD system, over an 18 hour period measured on a installed fiber with 5.5 dB attenuation.

Publisher

Optica Publishing Group

Reference3 articles.

1. Continuous-variable quantum key distribution under strong channel polarization disturbance

2. A polarization diversity CV-QKD detection scheme for channels with strong polarization drift;Pereira,2021

3. Unscented Kalman filters for polarization state tracking and phase noise mitigation

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1. CV-QKD in Coexistence with 1 Gb/s Classical Channel Using Electrical Frequency Division Multiplexing;2024 24th International Conference on Transparent Optical Networks (ICTON);2024-07-14

2. Intermode-interaction-induced dynamics of continuous-variable quantum-key-distribution observables;Physical Review A;2024-06-21

3. Continuous-variable quantum key distribution system: Past, present, and future;Applied Physics Reviews;2024-03-01

4. A Survey of Machine Learning Assisted Continuous-Variable Quantum Key Distribution;Information;2023-10-10

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