Reference-frame-independent quantum key distribution (RFI-QKD) has been proven to be intrinsically robust against slowly varying reference frames under realistic environment. In this paper, we propose a simplified scheme for the passive decoy-state RFI-QKD considering the afterpulsing effect. We investigated the system performance with the weak coherent source (WCS) and parametric down conversion (PDC) source, respectively. Numerical simulation results show that the simplified scheme can achieve comparable secure key rate with the active decoy-state scheme. Our scheme is advantageous to simplify the system implementation and reduces the time cost. Besides, it is proven that the afterpulsing effect plays dominant role in the system. Our work could provide a useful solution for RFI-QKD in practical situations.
The integration of quantum key distribution (QKD) devices with the existing optical fiber networks is of great significance in reducing the deployment costs and saving fiber resources. Wavelength division multiplexing (WDM) is expected to be a desirable approach to fulfill this ultimate task. In this paper, we analyze the dominant noises in WDM-based QKD system and optimize the key parameters based on a modified model with 200 GHz channel spacing. Then, an appropriate decoy-state method is adopted to estimate the system performance considering statistical fluctuations. Finally, a three-layer artificial neural network is used to train and predict the optimal mean photon numbers within different situations. Our work provides a useful method for the parameters optimization of WDM-QKD system and accelerates the practical development of QKD that coexists with the current backbone fiber infrastructure.
In order to study the influence of atmospheric turbulence on the polarization state of the free space quantum communication, the relationship between the refractive index and altitude, the refractive index structure constant and the turbulence dimension is deduced based on two different atmospheric refractive index structural constants models. The turbulence intensity factor κ is introduced and the equation of the variation of the quantum polarization degree with turbulence intensity is established. Through the simulation of the turbulent refractive index and the performance of four different polarization states in the low altitude turbulence environment, the results show that the atmospheric turbulence in the near ground will affect the fluctuation of the degree of polarization, and the degree of polarization varies linearly with the change of turbulence intensity. In the case of polarization |H>, the range of polarization |H> varies from 0 to 0.14 with the change of turbulence intensity. The influence of atmospheric turbulence on four different polarization states is different, and the degree of |H> and |V> depolarization is greater in the daytime and back. The depolarization degree of |-> at night is greater. The relationship between the degree of polarization and the change of turbulence intensity is analyzed by mathematical modeling, which is helpful to select the reasonable experimental scheme and compensate the change of polarization state in the aviation quantum Secure communication channel.
In order to improve the detection efficiency in QKD system, this paper has put forward a new quantum key distribution scheme based on the single photon frequency up-conversion detection technology and decoy-state BB84 protocol. A long wavelength pump light is adopted in single photon detector (SPD) to avoid the noise caused by spontaneous parametric down conversion (SPDC), thus an overall 28% detection efficiency is achieved which is five times of 4.5% in conventional InGaAs-based detectors. Moreover, the propagating distances has reached 90km and 150km with weak coherent pulse (WCP) and decoy weak coherent pulse (DWCP) respectively, which is 1.3 times and 1.05 times of the conventional InGaAs-based detectors of 70km and 140km.
State of polarization(SOP) of single photon is the information carrier of polarization encoding BB84 protocol. SOP of quantum must be interrupted when quantum key distribution(QKD) propagates with classical signal in the same fiber. Coexistence schemes of quantum-classical signal based on two-channel and four-channel have been built respectively on Optisystem in this paper. The influence on SOP of quantum signal in BB84 protocol from different classical optical signal channel has been analyzed and compared by Stokes vector method and Poincare sphere method. SOP of 100 photons in QKD have been simulated. The results show that more channels will increase the bit error rate of QKD, and this paper has described the SOP changes well in coexistence scheme of quantum-classical signal based on wavelength division multiplexing.
In visual tracking, deep learning with offline pretraining can extract more intrinsic and robust features. It has significant success solving the tracking drift in a complicated environment. However, offline pretraining requires numerous auxiliary training datasets and is considerably time-consuming for tracking tasks. To solve these problems, a multiscale sparse networks-based tracker (MSNT) under the particle filter framework is proposed. Based on the stacked sparse autoencoders and rectifier linear unit, the tracker has a flexible and adjustable architecture without the offline pretraining process and exploits the robust and powerful features effectively only through online training of limited labeled data. Meanwhile, the tracker builds four deep sparse networks of different scales, according to the target’s profile type. During tracking, the tracker selects the matched tracking network adaptively in accordance with the initial target’s profile type. It preserves the inherent structural information more efficiently than the single-scale networks. Additionally, a corresponding update strategy is proposed to improve the robustness of the tracker. Extensive experimental results on a large scale benchmark dataset show that the proposed method performs favorably against state-of-the-art methods in challenging environments.
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