IET Quantum Communication最新文献

Arecanut X-ray images accurately represent their internal structure. A comparative analysis of transfer learning-based classification, employing both a traditional convolutional neural network (CNN) and an advanced quantum convolutional neural network (QCNN) approach is conducted. The investigation explores various transfer learning models with different sizes to identify the most suitable one for achieving enhanced accuracy. The Shufflenet model with a scale factor of 2.0 attains the highest classification accuracy of 97.72% using the QCNN approach, with a model size of 28.40 MB. Out of the 12 transfer learning models tested, 9 exhibit improved classification accuracy when using QCNN models compared to the traditional CNN-based transfer learning approach. Consequently, the exploration of CNN and QCNN-based classification reveals that QCNN outperforms traditional CNN models in accuracy within the transfer learning framework. Further experiments with qubits suggest that utilising 4 qubits is optimal for classification operations in this context.

Quantum computing (QC) hinged upon the bedrock principles of quantum theory and holds promise for reforming a large number of industries. The researcher in this area aims to deliver a comprehensive understanding of the current state of the art and future trajectories of QC. The authors have discovered that most academic studies have concentrated upon dissecting specific aspects of QC. This discernment underscores the exigency of identifying challenges that might impede the seamless integration of QC within the software industry. Moreover, it becomes crucial to ascertain the panoply of solutions/practices required to overcome these barriers. A comprehensive multi-vocal literature review was performed and culled a total of 49 academic papers for data extraction. A total of 13 challenges encountered by organisations were identified during the adoption of QC. Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. These challenges from various perspectives were evaluated, including time frame, methodology, geographical region and publication platform. To address these barriers and implement the QC in software industry effectively, a total of 53 practices/solutions. This research aims to share valuable knowledge to simplify and amplify quantum application development.

The authors present a novel approach to Quantum Key Distribution (QKD) research, emphasising cost-effectiveness and practicality using a single photon polarisation-encoded system employing mainly commercial off-the-shelf components. This study diverges from previous high-cost, high-end setups by exploring the viability of QKD in more accessible and realistic settings. Our approach focuses on practical measurements of the signal-to-noise ratio by analysing polarisation-encoded photonic qubits over various transmission scenarios. The authors introduce a simplified evaluation method that incorporates experimental measurements, such as noise sources and losses, into a semi-empirical theoretical framework. This framework simulates the standard DS-BB84 protocol to estimate Secure Key Rates (SKRs), offering an alternative approach on the evaluation of the practical implementation of QKD. Specifically, the authors examine the feasibility of QKD over a 2.2 km intra-campus fibre link in coexistence scenarios, identifying optimal Wavelength-Division Multiplexing allocations to minimise Raman noise, achieving an expected SKR of up to 300 bps. Additionally, the authors’ study extends to 40 m indoor and 100 m outdoor Free-Space Optical (FSO) links using low-cost components, where the authors recorded Quantum Bit Error Rate (QBER) values below 3.2%, allowing for possible SKRs up to 600 bps even in daylight operation. The converged fibre/FSO scenario demonstrated robust performance, with QBER values below 3.7% and an expected SKR of over 200 bps. Our research bridges the gap between high-end and economical QKD solutions, providing valuable insights into the feasibility of QKD in everyday scenarios, especially within metropolitan fibre based and FSO links. By leveraging cost-effective components and a simplified single photon exchange setup, the authors work paves the way for the effortless characterisation of deployed infrastructure, highlighting its potential in diverse settings and its accessibility for widespread implementation.

Integration of Quantum Key Distribution (QKD) in existing telecommunication infrastructure is crucial for the widespread adoption of this quantum technology that offers the distillation of unconditionally secure keys between users. The authors report a field trial between the Points of Presence placed in Treviso and in Venezia—Mestre, Italy, exploiting the QuKy commercial polarisation-based QKD platforms developed by ThinkQuantum S.r.l. and two different standards of single-mode optical fibres, that is, G.652 and G.655 as a quantum channel. In this field trial, several configurations were tested, including the co-existence of classical and quantum signals over the same fibre, providing a direct comparison between the performances of the G.652 and G.655 fibre standards for QKD applications.

Artificial intelligence (AI) and classical machine learning (ML) techniques have revolutionised numerous fields, including quantum communication. Quantum communication technologies rely heavily on quantum resources, which can be challenging to produce, control, and maintain effectively to ensure optimum performance. ML has recently been applied to quantum communication and networks to mitigate noise-induced errors and analyse quantum protocols. The authors systematically review state-of-the-art ML applications to advance theoretical and experimental central quantum communication protocols, specifically quantum key distribution, quantum teleportation, quantum secret sharing, and quantum networks. Specifically, the authors survey the progress on how ML and, more broadly, AI techniques have been applied to optimise various components of a quantum communication system. This has resulted in ultra-secure quantum communication protocols with optimised key generation rates as well as efficient and robust quantum networks. Integrating AI and ML techniques opens intriguing prospects for securing and facilitating efficient and reliable large-scale communication between multiple parties. Most significantly, large-scale communication networks have the potential to gradually develop the maturity of a future quantum internet.

Quantum key distribution (QKD) provides a method of ensuring security using the laws of physics, avoiding the risks inherent in cryptosystems protected by computational complexity. Here, the authors investigate the feasibility of satellite-based quantum key exchange using low-cost compact nano-satellites. The first prototype of system level quantum key distribution aimed at the Cube satellite scenario is demonstrated. It consists of a transmitter payload, a ground receiver and simulated free space channel to verify the timing and synchronisation (T&S) scheme designed for QKD and the required high loss tolerance of both QKD and T&S channels. The transmitter is designed to be deployed on various up-coming nano-satellite missions in the UK and internationally. The effects of channel loss, background noise, gate width and mean photon number on the secure key rate (SKR) and quantum bit error rate (QBER) are discussed. The authors also analyse the source of QBER and establish the relationship between effective signal noise ratio (ESNR) and noise level, signal strength, gating window and other parameters as a reference for SKR optimisation. The experiment shows that it can tolerate the 40 dB loss expected in space to ground QKD and with small adjustment decoy states can be achieved. The discussion offers valuable insight not only for the design and optimisation of miniature low-cost satellite-based QKD systems but also any other short or long range free space QKD on the ground or in the air.

Entanglement-assisted quantum key distribution (QKD) has attracted significant attention for its ability to provide highly secure wireless systems. This work explores the employment of quantum teleportation and the quantum Fourier transform (QFT) in entanglement-assisted QKD to enhance security. By integrating the concepts of entanglement, teleportation, and QFT, the key distribution strategy is significantly improved, leading to more secure communication. The system has been thoroughly tested for quantum bit error rate, secure key rate, and reconciliation efficiency. The results show that this technique outperforms the standard BB84 protocol. Based on their simulations, this protocol appears to be a promising technique for providing quantum-level security to next-generation wireless communication systems.

Classical GAN architectures have shown interesting results for solving anomaly detection problems in general and for time series anomalies in particular, such as those arising in communication networks. In recent years, several quantum GAN (QGAN) architectures have been proposed in the literature. When detecting anomalies in time series using QGANs, huge challenges arise due to the limited number of qubits compared to the size of the data. To address these challenges, a new high-dimensional encoding approach, named Successive Data Injection (SuDaI) is proposed. In this approach, SuDaI explores a larger portion of the quantum state, compared to the conventional angle encoding method used predominantly in the literature. This is achieved through repeated data injections into the quantum state. SuDaI encoding allows the authors to adapt the QGAN for anomaly detection with network data of a much higher dimensionality than with the existing known QGANs implementations. In addition, SuDaI encoding applies to other types of high-dimensional time series and can be used in contexts beyond anomaly detection and QGANs, opening up therefore multiple fields of application.

In free-space implementations of Quantum key distribution (QKD), the wide adoption of near-Infrared wavelengths has led to the common use of silicon single-photon avalanche diodes (Si-SPAD) for receiver systems. While the impacts of some SPAD properties on QKD have been explored extensively, the relationship of spot-size and spatial position on the full instrumental response and thus quantum bit error rate (QBER) has been studied little. Changes in spot size and spatial position can result from atmospheric turbulence and pointing and tracking errors. Here, An empirical analysis of that relationship is presented utilising a large active area, 500 μm, free-space coupled Si-SPAD designed for free-space QKD. A baseline full-width at half-maximum timing jitter of 182 ps and a QBER contribution of 0.1 % for a 1 GHz clock frequency QKD system and 100 ps time-gating window are reported. The impacts of spot-size and spatial position can increase the QBER to over 0.3%. The link between the spot-size and timing jitter will allow the understanding of tolerancing for the alignment of Si-SPADs within free-space QKD receiver systems—an important factor in designing properly engineered practical systems and the equipment needed to compensate for atmospheric turbulence and pointing and tracking.

Teleporting energy to remote locations is new challenge for quantum information science and technology. Developing a method for transferring local energy in laboratory systems to remote locations will enable non-trivial energy flows in quantum networks. From the perspective of quantum information engineering, we propose a method for distributing local energy to a large number of remote nodes using hyperbolic geometry. Hyperbolic networks are suitable for energy allocation in large quantum networks since the number of nodes grows exponentially. To realise long-range quantum energy teleportation (QET), we propose a hybrid method of quantum state telepotation and QET. By transmitting local quantum information through quantum teleportation and performing conditional operations on that information, QET can theoretically be realized independent of geographical distance. The method we present will provide new insights into new applications of future large-scale quantum networks and potential applications of quantum physics to information engineering.