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International Conference on Computer Communication and Network Security (CCNS)

Dynamic polarization control optimization algorithm for quantum system in atmospheric channels

Jianmin Yi, Ying Guo

Published Aug 22, 2024• 0 citations
Publisher

Abstract

Using time and polarization multiplexing technology for transmission can reduce the interference of free space light on quantum signals. However, because of the presence of the free space channel, during light propagation, the polarization of light undergoes random fluctuations, causing substantial light leakage during direct polarization demultiplexing at the receiver, which can overpower the quantum signal. In this paper, we present an enhanced polarization control strategy leveraging a sophisticated algorithm, improving upon an existing dynamic polarization control approach. Through simulations, our proposal shows promising performance improvements. Our work focuses on the optimization of the control algorithm within the context of the previous dynamic polarization control strategy. After identifying limitations and issues in the original algorithm, we implemented a new optimization algorithm to address these problems. Simulations indicate that our optimized algorithm effectively reduces light leakage and provides fast and accurate response to changes in the polarization state of light.

DOI
10.1117/12.3038154

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Using time and polarization multiplexing technology for transmission can reduce the interference of free space light on quantum signals. However, because of the presence of the free space channel, during light propagation, the polarization of light undergoes random fluctuations, causing substantial light leakage during direct polarization demultiplexing at the receiver, which can overpower the quantum signal. In this paper, we present an enhanced polarization control strategy leveraging a sophisticated algorithm, improving upon an existing dynamic polarization control approach. Through simulations, our proposal shows promising performance improvements. Our work focuses on the optimization of the control algorithm within the context of the previous dynamic polarization control strategy. After identifying limitations and issues in the original algorithm, we implemented a new optimization algorithm to address these problems. Simulations indicate that our optimized algorithm effectively reduces light leakage and provides fast and accurate response to changes in the polarization state of light.
An available trick to mitigate the interference of environmental noise in quantum communications is to modulate signals with time-polarization multiplexing. Conversely, due to effects of the atmospheric turbulence in free space, the polarization of signals fluctuates randomly, resulting in feasible information leakage when direct polarization demultiplexing is carried out at the receiver, drowning out the noise-contained signals. For enhancing the practical security of the continuous-variable quantum key distribution (CVQKD), we propose a machine learning (ML) approach for optimization of the dynamic polarization control (DPC) of signals transmitted through atmospheric turbulence. An optimal DPC scheme can be adaptively adjusted with ML algorithms, which is based on the received signals at the receiver for solving the loophole problem of information leakage since it provides an accurate response to the polarization changes regarding the anamorphic signals. The performance of the CVQKD system can be increased in terms of secret key rates and maximal transmission distance as well. Numerical simulation shows the positive effect of the ML-based DPC while taking into account the secret key rate of the CVQKD system. The ML-based DPC effectively reduces the feasibility of information leakage and hence results in an increased secret key rate of the practical CVQKD system.
In a commercial fiber-based quantum key distribution system, the local and signal optical fields are transmitted through long distance fibers by using time division multiplexing and polarization multiplexing. The state of polarization of the optical field is inevitably disturbed by random birefringence of the standard single-mode fiber caused by external complex environments. This drift of the state of polarization significantly affects the balanced homodyne detection results and the secret key rate. Therefore, the key technology of the dynamic polarization control unit is crucial for the system in a large-scale commercial application. We theoretically analyze and prove that the polarization control unit only needs the combination of two degrees of freedom when considering the result of an arbitrary polarization extinction ratio at the receiver of the system. To overcome the influence of polarization variations, we propose a chaotic monkey algorithm based on Bayesian parameter estimation method and implement intelligence algorithm on field programmable gate array (FPGA) hardware under pulsed light with an integral-type detector for the dynamic polarization control unit. The simulation results show that the optimal combination is four degrees of freedom and the optimal prior distribution is an exponential distribution among various distributions in the dynamic polarization control unit. According to the simulation results, the experimental results show that the achieved polarization extinction ratio is over 30 dB and the average time of polarization control is 400 μs for a single random polarization scrambling. By combining the dynamic polarization control unit with the system, we demonstrate the continuous variable quantum key distribution (CV-QKD) under a continuous polarization scrambling scope of 0-2 krad/s and verify its effectiveness. In addition, the methods presented will improve the performance of the system and expand the range of applications even under strong external disturbance.
Quantum computing holds immense promise for scientific and technological advancements, but the inherent fragility of quantum systems necessitates robust error mitigation techniques. Conventional error mitigation strategies often rely on fixed parameters, failing to effectively address the complex and dynamic nature of quantum errors. This paper proposes a novel adaptive quantum error mitigation system utilizing a dynamic polarization control algorithm. We demonstrate the effectiveness of this approach through a rigorous analysis of quantum error propagation simulations, showcasing a significant improvement in fidelity compared to static mitigation methods. The core mechanism involves continuously monitoring the error rate and dynamically adjusting the polarization of quantum states, optimizing for maximal fidelity. This adaptive strategy represents a significant advancement in error mitigation, offering a flexible and potentially more effective solution for tackling the challenges of quantum computing.
Quantum sensing has performance advantages that far exceed classical sensing, where sensing with photons is one of the most useful branches, and fiberization is a significant development approach to achieve a broader range of applications. However, the birefringence effect in optical fibers can cause polarization drift, which severely reduces the sensitivity of measurement on weak signals and influences the development of quantum sensing. In order to solve this problem, we propose a scheme that builds four time-division-multiplexing channels in the system by switching the polarization states of different optical pulses, and achieves the effect of suppressing polarization drift by analyzing and integrating the effective information of the four polarization channels. Moreover, the sensitivity and linear dynamic range of the system can be adjusted by inserting a reference phase. We demonstrate the feasibility of the system via theoretical analysis, and the numerical simulation results show that the scheme can demodulate the signal well and improve the signal-to-noise ratio by 30 dB, even in the case of the signal of the direct demodulation method is drowned out by noise and completely distorted.
In free space channel, continuous-variable quantum key distribution (CV-QKD) using polarized coherent-states can not only make the signal state more stable and less susceptible to interference based on the polarization non-sensitive of the free-space channel, but also reduce the noise introduced by phase interference. However, arbitrary continuous modulation can not be carried out in the past polarization coding, resulting in that the signal state can not obtain arbitrary continuous value in Poincare space, and the security analysis of CV-QKD using polarized coherent-states in free space is not complete. Here we propose a new modulation method to extend the modulation range of signal states with an optical-fiber-based polarization controller. In particular, in terms of the main influence factors in the free-space channel, we utilize the beam extinction and elliptical model when considering the transmittance and adopt the formulation of secret key rate. In addition, the performance of the proposed scheme under foggy weather is also taken into consideration to reveal the influence of severe weather. Numerical simulation shows that the proposed scheme is seriously affected by attenuation under foggy weather. The protocol fails when visibility is less than 1 km. At the same time, the wavelength can affect the performance of the proposed scheme. Specifically, under foggy weather, the longer the wavelength, the smaller the attenuation coefficient, and the better the transmission performance. Our proposed scheme can expand the modulation range of signal state, and supplement the security research of the scheme in the free-space channel, thus can provide theoretical support for subsequent experiments.
This paper presents a novel approach to quantum information coding and decoding leveraging the unique properties of quantum entanglement. The core idea is to develop a self-adaptive system capable of dynamically adjusting encoding and decoding parameters based on the observed noise levels and channel losses within the quantum channel. This adaptive strategy aims to significantly improve the efficiency and reliability of quantum information transmission. The proposed framework utilizes a quantum decoherence model to accurately represent channel losses and employs an optimization algorithm rooted in quantum control theory to optimize the generation and measurement strategies of entangled states in real-time. The algorithm's objective is to minimize information loss. The key innovation lies in the system's ability to respond in real-time to fluctuating channel conditions, moving beyond the limitations of static encoding/decoding schemes commonly employed in existing quantum communication protocols. Mathematical models and formulations are presented to illustrate the design and optimization process, focusing on key performance metrics such as channel capacity and fidelity. The system's potential impact on future quantum communication networks is discussed.