Predicting atmospheric turbulence for secure quantum communications in free space
Abstract
Atmospheric turbulence is the main barrier to large-scale free-space quantum communication networks. Aberrations distort optical information carriers, thus limiting or preventing the possibility of establishing a secure link between two parties. For this reason, forecasting the turbulence strength within an optical channel is highly desirable, as it allows for knowing the optimal timing to establish a secure link in advance. Here, we train a Recurrent Neural Network, TAROCCO, to predict the turbulence strength within a free-space channel. The training is based on weather and turbulence data collected over 9 months for a 5.4 km intra-city free-space link across the City of Ottawa. The implications of accurate predictions from our network are demonstrated in a simulated high-dimensional Quantum Key Distribution protocol based on orbital angular momentum states of light across different turbulence regimes. TAROCCO will be crucial in validating a free-space channel to optimally route the key exchange for secure communications in real experimental scenarios.
Cite
@article{arxiv.2406.14768,
title = {Predicting atmospheric turbulence for secure quantum communications in free space},
author = {Tareq Jaouni and Lukas Scarfe and Frédéric Bouchard and Mario Krenn and Khabat Heshami and Francesco Di Colandrea and Ebrahim Karimi},
journal= {arXiv preprint arXiv:2406.14768},
year = {2025}
}