Designing a practical Continuous Variable (CV) Quantum Key Distribution (QKD) system requires an estimation of the quantum channel characteristics and the extraction of secure key bits based on a large number of distributed quantum signals. Meeting this requirement in short timescales is difficult. On standard processors, it can take several hours to reconcile the required number of quantum signals. This problem is exacerbated in the context of Low Earth Orbit (LEO) satellite CV-QKD, in which the satellite flyover time is constrained to be less than a few minutes. A potential solution to this problem is massive parallelisation of the classical reconciliation process in which a large-code block is subdivided into many shorter blocks for individual decoding. However, the penalty of this procedure on the important final secured key rate is non-trivial to determine and hitherto has not been formally analysed. Ideally, a determination of the optimal reduced block size, maximising the final key rate, would be forthcoming in such an analysis. In this work, we fill this important knowledge gap via detailed analyses and experimental verification of a CV-QKD sliced reconciliation protocol that uses large block-length low-density parity-check decoders. Our new solution results in a significant increase in the final key rate relative to non-optimised reconciliation. In addition, it allows for the acquisition of quantum secured messages between terrestrial stations and LEO satellites within a flyover timescale even using off-the-shelf processors. Our work points the way to optimised global quantum networks secured via fundamental physics.
翻译:设计实用的连续变量(CV) 量子键分布系统(QKD) 需要根据大量分布的量子信号对量子频道特性进行估计,并提取基于大量分布式量子信号的安全关键比特。 很难在短时间范围内满足这一要求。 在标准处理器上,可能需要几个小时才能调和所需的量子信号数量。 在低地球轨道(LEO)卫星CV-QKD范围内,卫星飞转时间限制不到几分钟的CV-QD 关键分布系统(QKD)系统中,这一问题将更加严重恶化。 这一问题的潜在解决办法是大规模平行的古典调和进程,在这个进程中,一个大编码的量子网络被细分成许多较短的块,供个人解码。 然而,这一程序对重要最终关键关键键率的处罚是非三重的,目前还没有正式分析。 理想的情况是,在这种分析中,将确定最佳的区块缩小规模,使最后关键键速率最大化。 在这项工作中,我们通过详细分析和实验核查一个CV-KD断切式的对量调进程内部的调进程,甚至使用大块式全球级的平比标准的升级的轨道上,从而使得我们最终的基数级的基数级的轨道获得结果能够大幅度地平价结果。