Practical Methods for Distance-Adaptive Continuous-Variable Quantum Key Distribution

TL;DR

This work analyzes the strict limitations on operating distance that are imposed by constant-rate FEC, severely limiting the practicability of CV-QKD systems in deployed optical networks, and evaluates three strategies: tuning modulation variance, adding controlled amounts of trusted detector loss, and the use of rate-adaptive FEC.

Abstract

Continuous-variable quantum key distribution (CV-QKD) is a promising quantum-safe alternative to classical asymmetric cryptography that enables two authenticated parties to establish a shared secret over a potentially eavesdropped quantum channel. A key step in CV-QKD post-processing is information reconciliation, which leverages forward error correction (FEC) techniques to extract identical bit strings from noisy correlated data. In this work, we analyze the strict limitations on operating distance that are imposed by constant-rate FEC, severely limiting the practicability of CV-QKD systems in deployed optical networks. To overcome the distance limitations, we evaluate three strategies: (i) tuning modulation variance, (ii) adding controlled amounts of trusted detector loss, and (iii) the use of rate-adaptive FEC. All approaches are validated experimentally, compared in terms of performance, and we discuss implementation aspects. Our results show that while methods (i) and (ii) extend the operational distance of constant-rate FEC without the need for additional hardware components, they incur a significant penalty in secret key rate (SKR). In contrast, rate-adaptive FEC enables CV-QKD operation with performance close to the asymptotic SKR over a wide range of distances, provided that the reconciliation efficiency is chosen appropriately.

Figures (13)

• Figure 1: Error correction for classical communications: mutual information $I_{\mathrm{AB}}$ and constant code rate $R_{\mathrm{c}}$ over the distance $d$ for a constant modulation variance.
• Figure 2: for : mutual information $I_{\mathrm{AB}}$, Holevo bound $\chi_{\mathrm{EB}}$ and constant code rate $R_{\mathrm{c}}$ over the distance $d$ for a constant modulation variance.
• Figure 3: Mutual information $I_{\mathrm{AB}}$ and Holevo bound $\chi_{\mathrm{EB}}$ over the distance $d$ when the modulation variance is tuned for constant received .
• Figure 4: Mutual information $I_{\mathrm{AB}}$ and Holevo bound $\chi_{\mathrm{EB}}$ over the distance $d$ when the trusted detector loss is scaled for constant received .
• Figure 5: Experimental setup for distance-adaptive . The investigated approaches ① to ③ are colored in blue, red and orange. The inset shows a qualitative plot of the acr:psd of the transmit signal, consisting of acr:fm-qpsk, acr:qkd and the digital acr:pt.