Pointing error directly limits QKD’s secure key throughput, affecting the viability of quantum‑secure networks in real‑world environments. Understanding and mitigating this impairment is essential for scaling quantum communications across free‑space and satellite links.
Quantum key distribution promises provably secure communication, but its practical deployment hinges on reliable free‑space optics. Mechanical vibrations, atmospheric turbulence, and imperfect alignment introduce pointing errors that scatter photons away from the receiver. Traditional analyses used oversimplified Gaussian models, obscuring the true impact of misalignment on photon detection statistics. By integrating Rayleigh and Hoyt distributions—well‑suited for horizontal and vertical beam deviations—the new framework delivers precise error probability estimates, enabling engineers to predict QBER and SKR with unprecedented fidelity.
The study’s analytical results reveal a clear trade‑off between beam geometry and system resilience. Expanding the beam waist to mitigate turbulence simultaneously amplifies pointing error, inflating QBER and throttling the secret key rate. Conversely, enlarging the receiver aperture captures more stray photons, yet gains plateau once diffraction limits dominate. Notably, asymmetric misalignment—where horizontal and vertical deviations differ—can lower QBER, suggesting that deliberately shaping beam profiles might offset some alignment imperfections. These insights guide the design of adaptive optics and tracking mechanisms for satellite‑to‑ground QKD links, where dynamic pointing errors are inevitable.
Beyond immediate engineering implications, the framework informs standards bodies and network planners about the photon budget required for reliable key generation. The finding that higher average photon numbers are necessary to sustain a non‑zero SKR under realistic pointing error conditions underscores the need for robust source engineering and error‑correction protocols. As quantum networks evolve toward global scale, incorporating such nuanced error models will be critical for achieving the high‑throughput, low‑latency performance demanded by financial, defense, and critical‑infrastructure sectors.
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