Discrete variables quantum key distribution (DV-QKD), with its well-studied and scrutinized BB84 protocol, benefits from being very attractive for highly secure communications. However, current detection schemes rely on the use of InGaAs SPDAs, which limits not only its use in high temperature environments, but also high secure communication rates. A possible approach is the use of coherent homodyne detection schemes for polarization encoding based DV-QKD combined. To deploy polarization encoding DV-QKD over standard optical fiber high speed networks, the polarization drift suffered due to birefringence over the channel must be compensated. In this work, we use a machine learning (ML) polarization tracking and compensation algorithm combined with a coherent homodyne receiver, thus allowing the deployment of high-speed polarization encoding based DV-QKD in standard optical fibers. The ML-algorithm predicts the SOP evolution keeping the error rate below 1 %. In this way, the overhead to polarization monitoring is reduced leading to a secure key exchange rate (SKR) of 79 Mbps for a communication over 40 km optical fiber.
Discrete variables quantum key distribution (DV-QKD), with its well-studied and scrutinized BB84 protocol, benefits from being very attractive for highly secure communications. However, current detection schemes rely on the use of InGaAs SPDAs, which limits not only its use in high temperature environments, but also high secure communication rates. A possible approach is the use of coherent homodyne detection schemes for polarization encoding based DV-QKD combined. To deploy polarization encoding DV-QKD over standard optical fiber high speed networks, the polarization drift suffered due to birefringence over the channel must be compensated. In this work, we use a machine learning (ML) polarization tracking and compensation algorithm combined with a coherent homodyne receiver, thus allowing the deployment of high-speed polarization encoding based DV-QKD in standard optical fibers. The ML-algorithm predicts the SOP evolution keeping the error rate below 1 %. In this way, the overhead to polarization monitoring is reduced leading to a secure key exchange rate (SKR) of 79 Mbps for a communication over 40 km optical fiber.
Secure communications have become a requirement for virtually all kind of applications. Currently, two distant parties can generate shared random secret keys by using public key cryptography. However, quantum computing represents one of the greatest threats for the finite complexity of the mathematics behind public key cryptography. In contrast, Quantum Key Distribution (QKD) relies on properties of quantum mechanics, which enables eavesdropping detection and guarantees the security of the key. Among QKD systems, polarization encoded QKD has been successfully tested in laboratory experiments and recently demonstrated in closed environments. In this paper, we propose a Machine Learning (ML) -based polarization tracking and compensation that is able to keep shared secret key exchange to high rates even under large fiber stressing events. Exhaustive results using both synthetic and experimental data show remarkable performance, which can simplify the design of both quantum transmitter and receiver, as well as enable the use of aerial optical cables, thus reducing total QKD system cost.
Optical homodyne detection is widely adopted in continuous-variable quantum key distribution for high-rate field measurement quadratures. Besides that, those detection schemes have been being implemented for single-photon statistics characterization in the field of quantum tomography. In this work, we propose a discrete-variable quantum key distribution (DV-QKD) implementation that combines the use of phase modulators for high-speed state of polarization (SOP) generation, with a conjugate homodyne detection scheme which enables the deployment of high speed QKD systems. The channel discretization relies on the application of a detection threshold that allows to map the measured voltages as a click or no-click. Our scheme relies also on the use of a time-multiplexed pilot tone-quantum signal architecture which enables the use of a Bob locally generated local oscillator and opens the door to an effective polarization drift compensation scheme. Besides that, our results shows that for higher detection threshold values we obtain a very low quantum bit error rate (QBER) on the sifted key. Nevertheless, due to huge number of discarded qubits the obtained secure key length abruptly decreases. From our results, we observe that optimizing the detection threshold and considering a system operating at 500 MHz symbol generation clock, a secure key rate of approximately 46.9 Mbps, with a sifted QBER of [Formula: see text] over 40 km of optical fiber. This considering the error correction and privacy amplification steps necessary to obtain a final secure key.
Secure communications have become a requirement for virtually all kind of applications. Currently, two distant parties can generate shared random secret keys by using public key cryptography. However, quantum computing represents one of the greatest threats for the finite complexity of the mathematics behind public key cryptography. In contrast, Quantum Key Distribution (QKD) relies on properties of quantum mechanics, which enables eavesdropping detection and guarantees the security of the key. Among QKD systems, polarization encoded QKD has been successfully tested in laboratory experiments and recently demonstrated in closed environments. The main drawback of QKD is its high cost, which comes, among others, from:i) the requirements for the quantum transmitters and receivers; andii) the need of carefully selecting the fibers supporting the quantum channel to minimize the environmental effects that could dramatically change the polarization state of photons. In this paper, we propose a Machine Learning (ML) -based polarization tracking and compensation that is able to keep shared secret key exchange to high rates even under large fiber stressing events. Exhaustive results using both synthetic and experimental data show remarkable performance, which can simplify the design of both quantum transmitter and receiver, as well as enable the use of aerial optical cables, thus reducing total QKD system cost.
Continuous-variable quantum key distribution (CV-QKD) provides a theoretical unconditionally secure solution to distribute symmetric keys among users connected through a communication channel. However, polarization drift in standard optical fibres can pose a considerable impairment, as it will degrade the efficiency of the coherent detection scheme if not compensated. In this work, we present a novel receiver configuration for CV-QKD that allows for passive polarization drift compensation. The presented results show that our detection system can effectively compensate random polarization drift even in very adverse scenarios.
Abstract The practical deployment of Continuous Variables Quantum Key Distribution (CV-QKD) systems benefits from existing optical fiber telecommunication infrastructures. However, optical fibers introduce random variations in the state of polarization, which degrades the system's performance.We consider a CV-QKD system featuring a polarization diversity heterodyne receiver and the constant modulus algorithm (CMA) to compensate for the polarization drifts in the quantum channel. Our setup can effectively realign Alice's quantum signal with Bob's local oscillator for polarization drift variances below 10−10 .This value is compatible with most experimental implementations, allowing for accurate estimation of the channel transmission and excess noise parameters. This validates the approximation of real-world implementations under polarization drift to an ideal scenario without polarization drift, ensuring that the security proof remains applicable for polarization drift variances below $ 10^{-10} $.Our results establish operational limits for passive polarization drift compensation using a polarization diversity receiver combined with digital CMA.This enables long-term stability in \linebreak CV-QKD systems, eliminating the need for active polarization controllers and manual adjustments.
Due to the fast-paced advancements of the quantum computing field, current public key cryptographic protocols need to be rethought. One promising solution is Quantum Key Distribution (QKD), whose security is robust to any computational advancement. The security of QKD relies on the laws of quantum mechanics, ensuring that any eavesdropper attempting to access the data will be detected. In particular, polarization-encoding QKD systems allow to generate secret keys in two remote locations to encode/decode information, using the State of Polarization (SOP) of single photons. Although its security has been theoretically proven, its practical implementation poses some challenges, part of which are the main focus of this PhD thesis. One relevant process in QKD systems is the synchronization between the transmitter and receiver, namely, the frame synchronization. This way, in this thesis, a frame synchronization method is developed and implemented, showing its potential for the use in prepare-and-measure QKD systems. The developed method has been shown to be effective, even with a low number of photons reaching the receiver. Furthermore, its architecture allows it to be adjusted for different attenuation regimes of the QKD system. The ability to encode data on the physical properties of single photons, in this case, polarization, highly depends on the capacity to accurately generate the required polarization states on demand. This way, an automatic SOP generation method, comprising an optical polarization monitoring system and a dedicated algorithm was developed and implemented, capable of generating four SOPs. This method reached an average Quantum Bit Error Rate (QBER) of 0.75%, which is well below the security threshold. After the SOP generation, and their transmission through the quantum channel, polarization alignment algorithms are required to compensate for the random rotations induced by birefringence in the optical fiber. In this thesis, a non-iterative polarization compensation method was implemented. This method requires only three QBER estimations to re-align the polarization, reaching average QBERs of 1.8%. Additionally, multiple iterative methods were implemented for comparison purposes, with the results clearly showing a better efficiency of the deterministic method. Beyond fiber-based transmissions, free-space transmissions were analysed due to their ability to reach sites without installed fiber and due to its potential for satellite-based quantum communications. This thesis demonstrates the feasibility of polarization-encoding QKD over free-space channels, by subjecting quantum signals to atmospheric turbulence to study its impact. In that sense, polarization variations over a 1.8 km outdoor free-space channel were monitored, to understand the effect of atmospheric turbulence on polarization. These results have shown that SOP variations in free-space links are slow, allowing their compensation. Furthermore, it was identified that, under conditions tested, the Secret Key Rate (SKR) could reach values up to 8.7×10ˉ⁴ bits per second, allowing QKD over free space for distances up to 2.31 km.