Security Analysis of MDI-QKD in Turbulent Free-Space Polarization Channels-A Composite Channel Framework
- URL: http://arxiv.org/abs/2509.02087v1
- Date: Tue, 02 Sep 2025 08:34:59 GMT
- Title: Security Analysis of MDI-QKD in Turbulent Free-Space Polarization Channels-A Composite Channel Framework
- Authors: Heyang Peng, Seid Koudia, Symeon Chatzinotas,
- Abstract summary: turbulence induces polarization decoherence and depolarization, which degrade the secret key rate.<n>We propose a unified depolarizing-dephasing channel model for turbulence-induced polarization decoherence in FSO MDI-QKD.<n>The model excels in clear, overcast, and hazy weather conditions, offering computational efficiency and experimental verifiability for real-time link adaptation.
- Score: 41.14912220553869
- License: http://creativecommons.org/publicdomain/zero/1.0/
- Abstract: Atmospheric turbulence poses a significant challenge to free-space measurement-device-independent quantum key distribution (FSO MDI-QKD) by inducing polarization decoherence and depolarization, which degrade the secret key rate (SKR). In this paper, we propose a unified depolarizing-dephasing channel model for turbulence-induced polarization decoherence in FSO MDI-QKD. This model consolidates phase perturbations, Gaussian beam spreading, beam drift, aperture truncation, and scintillation into closed-form parameters: depolarization factor, decoherence factor, and detection probability. By mapping turbulence to a von Mises-Fisher/Watson-distributed SU(2) rotation, we derive an analytic SKR expression compatible with existing MDI-QKD security analyses. The model excels in clear, overcast, and hazy weather conditions, offering computational efficiency and experimental verifiability for real-time link adaptation. Numerical simulations, illustrated on a ground-to-satellite free-space link, confirm its accuracy, enabling robust physical layer design for global-scale MDI-QKD networks.
Related papers
- Learning to Separate RF Signals Under Uncertainty: Detect-Then-Separate vs. Unified Joint Models [53.79667447811139]
We show that a single deep neural architecture learns to jointly detect and separate when applied directly to the received signal.<n>These findings highlight UJM as a scalable and practical alternative to DTS, while opening new directions for unified separation under broader estimation.
arXiv Detail & Related papers (2026-02-04T15:25:02Z) - SKANet: A Cognitive Dual-Stream Framework with Adaptive Modality Fusion for Robust Compound GNSS Interference Classification [47.20483076887704]
Global Navigation Satellite Systems (GNSS) face growing threats from sophisticated jamming interference.<n>We propose a cognitive deep learning framework built upon a dual-stream architecture that integrates Time-Frequency Images (TFIs) and Power Spectral Density (PSD)<n>We show that SKANet achieves an overall accuracy of 96.99%, exhibiting superior robustness for compound jamming classification.
arXiv Detail & Related papers (2026-01-19T07:42:45Z) - Engineering Si-Qubit MOSFETs: A Phase-Field Modeling Approach Integrating Quantum-Electrostatics at Cryogenic Temperatures [0.3015860973324597]
This study employs advanced phase-field modeling to investigate Si-based qubits.
We adopt a comprehensive modeling approach, utilizing full-wave treatment of the Schrodinger equation solutions, coupled with the Poisson equation at cryogenic temperatures.
arXiv Detail & Related papers (2024-10-06T03:25:07Z) - Security Loophole Induced by Photorefractive Effect in Continous-variable Quantum Key Distribution System [4.7922744779403015]
We analyzed the security loophole of CVQKD under the photorefractive effect (PE)
It is found that the refractive index change of modulators because of PE may lead to an overestimate or underestimate of the final secret key rate.
arXiv Detail & Related papers (2024-08-31T16:25:54Z) - Time-inversion of spatiotemporal beam dynamics using uncertainty-aware latent evolution reversal [46.348283638884425]
This paper introduces a reverse Latent Evolution Model (rLEM) designed for temporal phase of forward beam dynamics.
In this two-step self-supervised deep learning framework, we utilize a Conditional Autoencoder (CVAE) to project 6D space projections of a charged particle beam into a lower-dimensional latent distribution.
We then autoregressively learn the inverse temporal dynamics in the latent space using a Long Short-Term Memory (LSTM) network.
arXiv Detail & Related papers (2024-08-14T23:09:01Z) - Coherent Detection of Discrete Variable Quantum Key Distribution using
Homodyne Technique [0.18749305679160366]
Homodyne detection method is frequently employed for its simplicity in use, effectiveness in terms of error correction, and suitability with contemporary optical communication systems.
We present simulation results for System Efficiency and Quantum Bit Error Rate (QBER) for the proposed model.
arXiv Detail & Related papers (2024-02-20T15:39:50Z) - Ensemble Kalman Filtering Meets Gaussian Process SSM for Non-Mean-Field and Online Inference [47.460898983429374]
We introduce an ensemble Kalman filter (EnKF) into the non-mean-field (NMF) variational inference framework to approximate the posterior distribution of the latent states.
This novel marriage between EnKF and GPSSM not only eliminates the need for extensive parameterization in learning variational distributions, but also enables an interpretable, closed-form approximation of the evidence lower bound (ELBO)
We demonstrate that the resulting EnKF-aided online algorithm embodies a principled objective function by ensuring data-fitting accuracy while incorporating model regularizations to mitigate overfitting.
arXiv Detail & Related papers (2023-12-10T15:22:30Z) - Experimental decoy-state asymmetric measurement-device-independent
quantum key distribution over a turbulent high-loss channel [0.0]
Measurement-Device-Independent (MDI) QKD authorizes an untrusted third party to make measurements and removes all side-channel attacks.
We demonstrate enhancement in the secure key rate under turbulent conditions for finite-size decoy-state MDI QKD.
arXiv Detail & Related papers (2023-11-07T20:36:33Z) - Macroscopic noise amplification by asymmetric dyads in non-Hermitian
optical systems for generative diffusion models [55.2480439325792]
asymmetric non-Hermitian dyads are promising candidates for efficient sensors and ultra-fast random number generators.
integrated light emission from such asymmetric dyads can be efficiently used for all-optical degenerative diffusion models of machine learning.
arXiv Detail & Related papers (2022-06-24T10:19:36Z) - Locality of Spontaneous Symmetry Breaking and Universal Spacing
Distribution of Topological Defects Formed Across a Phase Transition [62.997667081978825]
A continuous phase transition results in the formation of topological defects with a density predicted by the Kibble-Zurek mechanism (KZM)
We characterize the spatial distribution of point-like topological defects in the resulting nonequilibrium state and model it using a Poisson point process in arbitrary spatial dimension with KZM density.
arXiv Detail & Related papers (2022-02-23T19:00:06Z) - Feasibility of space-based measurement-device-independent quantum key
distribution [11.12868147408137]
We present a feasibility assessment of space-based MDI-QKD based on the Micius satellite.
Our work can be used as a pathfinder to support decisions involving as the selection of the future quantum communication satellite missions.
arXiv Detail & Related papers (2020-12-29T01:24:27Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.