Robust and cost-effective quantum network using Kramers-Kronig receiver

TL;DR

This work first proposes a continuous-variable QKD protocol based on direct detection without interference, which achieves the recovery of quadrature components through the Kramers-Kronig relation and extends this protocol to continuous-variable quantum access networks, further highlighting the robustness and cost advantages of interference-free detection.

Abstract

The quantum internet holds the potential to facilitate applications that are fundamentally inaccessible to the classical internet. Among its most prominent applications is quantum key distribution (QKD) networks, which connect two distant nodes to establish a secure key based on the principles of quantum mechanics. However, the subsequent extensive reliance on interferences in existing QKD protocols leads to the weak robustness of the system and the corresponding network. In this work, we propose a robust and cost-effective quantum network using the Kramers-Kronig receiver. We first propose a continuous-variable QKD protocol based on direct detection without interference, which achieves the recovery of quadrature components through the Kramers-Kronig relation. Subsequently, we have extended this protocol to continuous-variable quantum access networks, further highlighting the robustness and cost advantages of interference-free detection. The experimental results show that each user can achieve a secret key rate at 50 kbit/s within the access network range by using only one photodetector without interference structures. This scheme opens up new possibilities in establishing a robust and cost-effective quantum network, serving as a foundational element in the progress toward establishing a large-scale quantum internet.

Figures (5)

• Figure 1: Equivalent representation of the image-band vacuum fluctuation.
• Figure 2: Schematic of the DD CV-QAN system. (ISO: isolator; IQM: IQ modulator; VOA: variable optical attenuator; PD: photodetector; AWG: arbitrary waveform generator; ABC: automatic bias controller; OSC: oscilloscope; SMF: single-mode fiber).
• Figure 3: Data recovery results of DD CV-QAN. Here real and imag denote the real and imaginary parts respectively. (a) The partial time-domain waveform of the intensity signal. (b) The partial time-domain waveform of the minimum-phase signal. (c) The partial time-domain waveform of the recovery signal. (d) The bivariate distribution histogram of the Gaussian data obtained from a frame of received signal. (e) Cross-correlation function between the received data series and the transmitted data series. The cross-correlation function is normalised in such a way that the zero-lag autocorrelation is equal to one. (f) The raw secret key shared by QLT and one of QNUs
• Figure 4: Excess noise data plots for four users. The horizontal dotted line represents the average excess noise for each user. The shaded areas in each figure represent the data range. (a) The excess noise data for user 1 is represented by blue asterisks. (b) The excess noise data for user 2 is represented by red circles. (c) The excess noise data for user 3 is represented by green squares. (d) The excessive noise data for user 4 is represented by magenta triangles.
• Figure 5: Experimental results of 4-user DD CV-QAN. The blue line, red line, green line, and magenta line represent the SKR curves of user 1, user 2, user 3, and user 4, respectively. The solid line, dashed line, and dash-dot line represent the SKR curves of the asymptotic case, $10^9$ blocks length case, and $10^8$ blocks length case, respectively.