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<p>Quantum key distribution (QKD) leverages the principles of quantum mechanics to generate unconditionally secure keys for remote communication, even in the presence of an eavesdropper with unlimited computational power. A critical component of QKD is information reconciliation (IR), which corrects bit errors introduced by system imperfections and channel noise, ensuring the integrity of the shared key. Polar codes-based IR schemes have attracted considerable attention due to their near-Shannon-limit performance and low computational complexity. However, existing implementations primarily rely on CPUs or GPUs, which are suboptimal in terms of performance and energy efficiency. Here, we present a hardware accelerator designed specifically for discrete variable QKD (DV-QKD), targeting polar codes-based IR and implemented on a cost-effective FPGA platform. Our design achieves high throughput and scalability by employing a module-level pipeline parallel structure, a fully parallelized decoding strategy, and a hybrid memory architecture. This approach enhances decoder efficiency and optimizes resource utilization. On this platform, we demonstrate an IR throughput of 35.33 Mbps for a block size of <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41598_2025_20146_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="21" /> </InlineMediaObject> <EquationSource Format="TEX">\(2^{20}\)</EquationSource> </InlineEquation>, providing a real-time, cost-efficient solution that significantly enhances the performance of QKD systems.</p>

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Efficient FPGA implementation of polar codes-based information reconciliation for quantum key distribution

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月16日

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  • Lianye Liao,
  • Xinyi Wu,
  • Ye Chen,
  • Xiaodong Fan,
  • Zhiyu Tian,
  • Jinquan Huang,
  • Tonglin Mu,
  • Junran Guo,
  • Minjie Liu,
  • Bo Liu,
  • Shihai Sun

摘要

Quantum key distribution (QKD) leverages the principles of quantum mechanics to generate unconditionally secure keys for remote communication, even in the presence of an eavesdropper with unlimited computational power. A critical component of QKD is information reconciliation (IR), which corrects bit errors introduced by system imperfections and channel noise, ensuring the integrity of the shared key. Polar codes-based IR schemes have attracted considerable attention due to their near-Shannon-limit performance and low computational complexity. However, existing implementations primarily rely on CPUs or GPUs, which are suboptimal in terms of performance and energy efficiency. Here, we present a hardware accelerator designed specifically for discrete variable QKD (DV-QKD), targeting polar codes-based IR and implemented on a cost-effective FPGA platform. Our design achieves high throughput and scalability by employing a module-level pipeline parallel structure, a fully parallelized decoding strategy, and a hybrid memory architecture. This approach enhances decoder efficiency and optimizes resource utilization. On this platform, we demonstrate an IR throughput of 35.33 Mbps for a block size of \(2^{20}\) , providing a real-time, cost-efficient solution that significantly enhances the performance of QKD systems.