连续变量量子密钥分发与远距离下的密钥率远超PLOB界限
Continuous-Variable Quantum Key Distribution with key rates far above the PLOB bound
AI总结：
本文提出了一种连续变量量子密钥分发的逆向 reconciliation 方案，通过随机码本纠错在香农极限之上实现远超PLOB界限的密钥率。
摘要：
连续变量量子密钥分发（CVQKD）在远距离下具有如此高的噪声水平，使得纠错码必须具有非常低的速率。在这种情况下，实施随机码本纠错变得可行，而这种纠错方式已知接近容量。我们提出了一种用于CVQKD的逆向 reconciliation 方案，在第一步中基于随机码本纠错进行优势蒸馏，该纠错在香农极限之上运行。我们的方案具有实现公共 reconciliation 数据与秘密密钥之间统计解耦的新方法。我们对高斯集体攻击情况下的秘密密钥率进行了分析，并提供了数值结果。当信息量超过Alice的四度X和Bob的测量Y之间的互信息I(X;Y)时，即香农极限，获得最佳性能。这一有些反直觉的结果源于码率与帧拒绝率之间的权衡，再加上量子密钥分发中的纠错只需重合随机数据的事实。我们获得的秘密密钥率远超Devetak-Winter值I(X;Y) - I(E;Y)，这是单向纠错情况下的上限。此外，我们的密钥率远超连续变量检测的PLOB界限，但低于离散变量检测的PLOB界限。
英文摘要：
Continuous-Variable Quantum Key Distribution (CVQKD) at large distances has such high noise levels that the error-correcting code must have very low rate. In this regime it becomes feasible to implement random-codebook error correction, which is known to perform close to capacity. We propose a reverse reconciliation scheme for CVQKD in which the first step is advantage distillation based on random-codebook error correction operated above the Shannon limit. Our scheme has a novel way of achieving statistical decoupling between the public reconciliation data and the secret key. We provide an analysis of the secret key rate for the case of Gaussian collective attacks, and we present numerical results. The best performance is obtained when the message size exceeds the mutual information $I(X;Y)$ between Alice's quadratures $X$ and Bob's measurements $Y$, i.e. the Shannon limit. This somewhat counter-intuitive result is understood from a tradeoff between code rate and frame rejection rate, combined with the fact that error correction for QKD needs to reconcile only random data. We obtain secret key rates that lie far above the Devetak-Winter value $I(X;Y) - I(E;Y)$, which is the upper bound in the case of one-way error correction. Furthermore, our key rates lie above the PLOB bound for Continuous-Variable detection, but below the PLOB bound for Discrete-Variable detection.
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