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    From uniformity to fluctuations: Quantifying the security cost of imperfect randomness in quantum key distribution

    Andrei Gaidash1, Pavel Yakovlev2, George Miroshnichenko3, and Anton Kozubov1,*

    • 1SMARTS-Quanttelecom LLC, 199178, 59-1-B 6th line of Vasilievsky Island, Saint Petersburg, Russia and Laboratory of Quantum Processes and Measurements, ITMO University, 3b Kadetskaya Line, 199034 Saint Petersburg, Russia
    • 2St. Petersburg State University, 7–9, Universitetskaya nab., 199034 Saint Petersburg, Russia
    • 3Waveguide Photonics Research Center, ITMO University, 49 Kronverksky Prospekt, 197101 Saint Petersburg, Russia and Institute “High School of Engineering,” ITMO University, 49 Kronverksky Prospekt, 197101 Saint Petersburg, Russia

    • *Contact author: avkozubov@itmo.ru

    Phys. Rev. A 113, 032612 – Published 11 March, 2026

    DOI: https://doi.org/10.1103/nqpb-8h13

    Abstract

    In this work, we examine the impact of imperfect randomness on the security of quantum key distribution (QKD) protocols with a set of linearly independent states, with particular emphasis on deviations from uniform a priori probabilities in quantum state preparation. Both stationary and nonstationary forms of randomness imperfections are considered. In the stationary case—where the preparation probabilities remain constant throughout the entire sequence—we demonstrate that increasing asymmetry monotonically decreases the source entropy and the Holevo information, thereby reducing the conditional entropy and the extractable secret key length. We also explicitly quantify the impact of preparation bias on the achievable secret key rate in protocols based on linearly independent states. In contrast, the non–independent and identically distributed regime, characterized by signalwise fluctuations in the a priori probabilities, is shown to yield a reduction in conditional entropy proportional to the second moment of the deviation distribution, assuming small perturbations. We further analyze several representative classes of biased distributions, establishing upper and lower bounds on the corresponding conditional entropies. These results highlight the necessity of rigorously accounting for randomness imperfections in practical QKD systems and suggest concrete strategies for adjusting key length estimation under realistic, nonideal conditions.

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