高斯量子密钥分发数据协调的性能优化  

Performance Optimization for the Reconciliation of Gaussian Quantum Key Distribution

作　　者：郭大波[1] 张彦煌[1] 王云艳[1] 

机构地区：[1]山西大学物理电子工程学院,山西太原030006

出　　处：《光学学报》2014年第1期225-231,共7页Acta Optica Sinica

基　　金：量子光学与光量子器件国家重点实验室开放基金(KF201003)

摘　　要：针对高斯量子密钥分发的数据协调问题,对高斯连续变量进行了最优量化,实现了Alice和Bob之间的互信息量最大。在分层错误校正(SEC)协议和多电平编码/多级解码(MLC/MSD)协议的基础上,各级码流采用了低密度奇偶校验码(LDPC)进行错误校正,并推出了一次硬信息级间迭代更新公式参与MSD译码算法。算法实现中使用双向十字链表方式存贮LDPC码的稀疏矩阵H,并用C语言实现整个数据协调过程,极大地降低了空间复杂度,提高了协调速度。实验仿真结果表明该算法可在信道信噪比4.9dB以上实现2×105个连续变量序列的可靠协调,协调效率达91.71%,在2.4GHz CPU,32G内存服务器平台上的协调速度可达7262bit/s。For reconciliation of Gaussian quantum key distribution, optimal quantization intervals of continuous variables are searched to maximize the mutual information between Alice and Bob. Based on both sliced error correction （SEC） and multilevel coding/multistage decoding （MLC/MSD） protocols, low density parity check （LDPC） is employed in each level of coding streams. A one-time multistage iterative information update formula for MSD algorithm is also derived. In the implementation, double cross-linked list is used to store sparse matrix H of LDPC. C language is also used to realize the whole reconciliation process. These greatly reduce space complexity and speed up reconciliation process. Simulation results show that the proposed algorithm can reconcile 2×109 continuous quantum variables reliably when signal-to-noise ratio of receiver is above 4.9 dB, with reconciliation efficiency of 91.71%. On a server with 2.4 GHz CPU and 32 G memory, the speed of the reconciliation reaches 7262 bit/s.

关 键 词：量子光学 量子密钥分发 数据协调 最优量化 低密度校验码 稀疏矩阵 

分 类 号：O431[机械工程—光学工程]