Quantum key distribution (QKD) has emerged as a promising solution to protect current cryptographic systems against the threat of quantum computers. As QKD transitions from laboratories to real-world applications, its implementation under various environmental conditions has become a pressing challenge. Major obstacles to practical QKD implementation are the loss of photons in the transmission media and the presence of extreme noise, which can severely limit long-range transmission. In this paper, we investigate the impact of extreme noise on QKD system parameters, including timing jitter, rate-dependent timing shifts, changes in effective detector dead time, and rate-dependent detection efficiency. Contrary to manufacturers' specifications, which assume these parameters to be constant, we demonstrate that these parameters exhibit significant variations in extreme noise conditions. We show that changes in these parameters play a key role in determining system performance in noisy environments. To address these nonidealities, we develop a model that adapts to detector-dependent timing distortions and recovery effects. In particular, our model is independent of source parameters and can be implemented using data from the detection unit. Our results show that the model enables reliable characterization and optimization of QKD performance under strong noise.
Quantum key distribution (QKD) has emerged as a promising solution to protect current cryptographic systems against the threat of quantum computers. As QKD transitions from laboratories to real-world applications, its implementation under various environmental conditions has become a pressing challenge. Major obstacles to practical QKD implementation are the loss of photons in the transmission media and the presence of extreme noise, which can severely limit long-range transmission. In this paper, we investigate the impact of extreme noise on QKD system parameters, including timing jitter, rate-dependent timing shifts, changes in effective detector dead time, and rate-dependent detection efficiency. Contrary to manufacturers' specifications, which assume these parameters to be constant, we demonstrate that these parameters exhibit significant variations in extreme noise conditions. We show that changes in these parameters play a key role in determining system performance in noisy environments. To address these nonidealities, we develop a model that adapts to detector-dependent timing distortions and recovery effects. In particular, our model is independent of source parameters and can be implemented using data from the detection unit. Our results show that the model enables reliable characterization and optimization of QKD performance under strong noise.
Quantum key distribution (QKD) allows unconditionally secure communication based on the laws of quantum mechanics rather than assumptions about computational hardness. Optimizing the operation parameters of a given QKD implementation is indispensable in order to achieve high secure key rates. So far, there exists no model that accurately describes entanglement-based QKD with continuous-wave pump lasers. We analyze the underlying mechanisms for QKD with temporally uniform pair-creation probabilities and develop a simple but accurate model to calculate optimal tradeoffs for maximal secure key rates. In particular, we find an optimization strategy of the source brightness for given losses and detection-time resolution. All experimental parameters utilized by the model can be inferred directly in standard QKD implementations, and no additional assessment of device performance is required. Comparison with experimental data shows the validity of our model. Our results yield a tool to determine optimal operation parameters for already existing QKD systems, to plan a full QKD implementation from scratch, and to determine fundamental key rate and distance limits of given connections.
Abstract Quantum Key Distribution (QKD) is a cornerstone of next-generation cryptographic technologies, offering unparalleled security by utilizing the principles of quantum mechanics. However, practical implementations of QKD face significant challenges, including inefficiencies in key generation, susceptibility to noise, and vulnerabilities to eavesdropping. This work addresses these challenges by proposing a machine learning (ML)-driven approach to optimize QKD protocols, focusing on enhancing both efficiency and security. In this work it is intended to evaluate three advanced protocols Adaptive, Entanglement-Based, and Hybrid under varying conditions such as key length, noise levels, and channel stability. The ML models will include ensemble learning models namely Random Forest and XGBoost, the models will analyze the impact of key parameters on protocol performance and predict efficiency with high accuracy. The results reveal that the Adaptive protocol significantly outperforms the Entanglement-Based and Hybrid protocols, achieving an efficiency of up to 0.80 for a key length of 2500 bits, compared to 0.24 for the Entanglement-Based protocol and 0.26 for the Hybrid protocol. The Adaptive protocol also demonstrates superior detection probability (ranging from 0.84 to 0.85) and a higher probability of detecting eavesdropping (ranging from 0.43 to 0.45). Furthermore, correlation analysis shows a strong positive relationship (r = 0.9985) between key length and efficiency for the Adaptive protocol, highlighting its scalability. In contrast, the Entanglement-Based protocol shows consistent but lower performance across all metrics, while the Hybrid protocol offers a compromise but remains less efficient than the Adaptive protocol. By integrating ML with quantum cryptography, this work bridges the gap between theoretical advancements and practical implementations, providing a scalable framework for optimizing QKD systems in real-world applications. The findings underscore the importance of protocol design and optimization in achieving secure and efficient quantum communication, paving the way for the quantum internet of the future.
Abstract In this paper, we present a comprehensive investigation of subcarrier wave quantum key distribution (SCW QKD) application to ship-to-port links. Our analysis specifically addresses the critical challenges inherent to maritime environments, particularly the complex interplay between atmospheric turbulence and fog-induced visibility reduction. We demonstrate the significant influence of these environmental factors on both the quantum bit error rate and secure key generation rate. We present insights into the critical trade-offs between detector types, offering strategies to mitigate noise while maximizing efficiency. Our research introduces a methodology for modeling transmittance and noise effects, which we have developed to incorporate turbulence loss coefficients, extinction models, and thermal photon noise. Importantly, we employ finite-key security analysis to ensure our findings reflect robust system performance under real-world conditions. We show that by leveraging high spectral efficiency and adaptability, SCW QKD emerges as a compelling solution for extending quantum communications across various free-space environments, including satellite applications and moving devices.
Recent advances in quantum key distribution (QKD) have given rise to systems that operate at transmission periods significantly shorter than the dead times of their component single-photon detectors. As systems continue to increase in transmission rate, security concerns associated with detector dead times can limit the production rate of sifted bits. We present a model of high-speed QKD in this limit that identifies an optimum transmission rate for a system with given link loss and detector response characteristics.
Entanglement-based quantum key distribution (QKD) protocols, such as E91 and BBM92, offer strong information-theoretic security and are naturally suited for satellite-to-satellite QKD (SatQKD) links. However, implementing these protocols over long-distance inter-satellite free-space optical (FSO) channels poses critical physical-layer challenges that are not addressed in the existing literature. In particular, photon losses due to beam divergence, pointing errors, and background noise can severely degrade the key generation rate and quantum bit error rate (QBER), especially under narrow receiver field-of-view (FoV) constraints. This paper presents a comprehensive performance analysis of entanglement-based inter-satellite QKD, focusing on photon-level modeling and the impact of practical impairments. We develop analytical expressions for signal detection probabilities, background photon influence, multi-pair emissions, and QBER, incorporating key parameters such as link distance, transmitter tracking jitter, receiver misalignment, and photon pair generation rate. Simulation results reveal the nonlinear sensitivity of system performance to tracking error and FoV limitations, and highlight optimal parameter regimes that jointly maximize secret key rate while maintaining QBER below acceptable thresholds. The proposed model provides actionable design insights for reliable and efficient deployment of entanglement-based SatQKD systems.
A precise estimation of the detection response is essential for a high-performance and secure quantum-key-distribution (QKD) system. Single-photon avalanche diodes (SPADs) are widely applied to estimate the single-photon yields. However, in the presence of the dead time and afterpulse of the SPADs, the estimations of gains in previous models are biased, which will lead to ill-fitting optimized parameters and greatly degrade the system performance. Here, we develop a dependency model for providing more accurate optimization to achieve higher-performance QKD systems. Moreover, to further improve the system performance, our model guides users to choose proper dead time. Our simulation results indicate that our model plays an important role in the practical application and deployment of QKD systems.