ABSTRACT Retinopathy of prematurity (ROP) is a serious eye disease for premature infants. One of the main reasons for ROP is the use of oxygen for prolonged periods. In ROP, the abnormal blood vessels extend into the vitreous, the gel‐like substance, and the retina may become partially detached with the formation of a ridge. Early detection and treatment of ROP are important to prevent blindness. This work aims (i) to classify normal and ROP‐affected retinal images using a quantum neural network (QNN) and (ii) to compare the performance of the proposed quantum ROP (QROP) system with the existing ROP identification methods. QROP uses the HVDROPDB dataset fundus images of preterm infants. These images are captured using RetCam and Neo imaging devices. Only 15 parameters and a few samples extracted from the database were used for model training to achieve desirable evaluation metrics of accuracy, precision, sensitivity, F1‐score and specificity. The proposed system achieves 97.06% accuracy with the HVDROPDB Neo dataset, 91.18% accuracy with the HVDROPDB RetCam dataset, and 85.29% accuracy when evaluated on the images from variable imaging devices and of different resolutions.

ABSTRACT In this paper, we introduce an improved spontaneous Raman scattering (SRS) model to accurately determine the quantum communication channel's quality when integrated into a Dense Wavelength Division Multiplexing (DWDM) network. To assess the degradational effect of counter‐propagating SRS, we carried out laboratory experiments to analyse the impact of different variables, namely the input power, fibre length and channel arrangement. Based on the measurement results, we developed a new model for defining SRS within the C‐band, which provides more precision in describing the impact of SRS compared to the previously used simplified V‐shape model. A 96‐channel DWDM use case, including one quantum and 90 classical channels, is modelled to identify the optimal channel wavelength allocation strategy. Using the revised model, we concluded that the optimal channel layout, where the channel numbering is based on the ITU‐T standard, is with the quantum channel being the 88th (1533.4 nm), or the 96th (1530.2 nm) if we consider the classical capacity. In contrast, if the V‐shape model is used for defining the optimal channel allocation, the quantum channel would be the 59th (1545 nm). The results show the importance of accurately modelling SRS, as determining the right channel placement is essential for the coexistence of quantum and classical channels.

ABSTRACT Quantum key distribution (QKD) has often been hailed as a reliable technology for secure communication in cyber–physical microgrids. Even though unauthorised key measurements are not possible in QKD, attempts to read them can disturb quantum states leading to mutations in the transmitted value. Further, inaccurate quantum keys can lead to erroneous decryption producing garbage values, destabilising microgrid operation. QKD can also be vulnerable to node‐level manipulations incorporating attack values into measurements before they are encrypted at the communication layer. To address these issues, this paper proposes a secure QKD protocol that can identify errors in keys and/or nodal measurements by observing violations in control dynamics. Additionally, the protocol uses a dynamic adjacency matrix‐based formulation strategy enabling the affected nodes to reconstruct a trustworthy signal and replace it with the attacked signal in a multi‐hop manner. This enables microgrids to perform nominal operations in the presence of adversaries who try to eavesdrop on the system causing an increase in the quantum bit error rate (QBER). We provide several case studies to showcase the robustness of the proposed strategy against eavesdroppers and node manipulations. The results demonstrate that it can resist unwanted observation and attack vectors that manipulate signals before encryption.

ABSTRACT Medical image integrity is critical as telemedicine, cloud PACS and AI‐assisted diagnostics become routine. We present a tamper localisation framework that embeds authentication signatures in the phase domain of blockwise quantum Fourier transform (QFT) coefficients. The watermark is phase‐only, energy preserving and keyed through sparse midband supports with paired phase differences; a light cross‐block coupling imposes spatial consistency so that localised edits produce coherent high‐contrast residuals confined to manipulated regions after inverse QFT. Because magnitudes remain unaltered, benign photometric variations are naturally attenuated, improving specificity under common acquisition and storage pipelines. The verifier computes circular phase residuals and applies an adaptive threshold to generate blockwise tamper maps, which are refined to pixel resolution. Across standard distortions (JPEG recompression, Gaussian noise and blur) and localised forgeries (copy–move, inpainting and contrast edits), the scheme maintains diagnostic fidelity (typical PSNR 40 dB, SSIM 0.98) while delivering precise spatially resolved detection. The design is deterministic and reproducible via seeded keys, integrates with DICOM workflows and is amenable to future quantum hardware realisation. This work contributes a quantum‐ready, imperceptible and localisation‐oriented approach to medical image authentication suitable for deployment in modern healthcare systems. The proposed QFT phase–only watermark achieves imperceptibility (global PSNR dB; SSIM ) and detects localised tampering (ROC AUC under class imbalance).

ABSTRACT Transforms play a pivotal role in the study of signals and images. With the advent of quantum systems, analysing signals in the quantum domain is of particular interest. In this work, we aim to build a generalised transform circuit in the quantum domain. We have shown the working of this circuit for Wavelet transform, Fourier transform, and Discrete Cosine Transform (DCT) on vector, matrix, and an image respectively. We also take inverse transforms in each of the cases to match with the given initial input. We use simulators for this work, and the results obtained are favourable. We further use this circuit for classification of heart beats as it is an essential task in detection of cardiac diseases. We utilise both classical and quantum computation to classify beats of Electrocardiogram (ECG, hereafter) signals into normal and not‐normal beats (non‐beats and abnormal beats). This novel architecture to carry out transform is quite general and can be used for any arbitrary transform.

ABSTRACT We propose a novel procedure for generating an arbitrary energy eigenstate from physical states. To validate it, we demonstrate the generation of an energy eigenstate of the molecule from a superposition of energy eigenstates by classically emulated quantum simulation. We use a Hamiltonian represented by Pauli matrices and concatenated ancilla qubits. Starting from an adequate initial state of physical qubits, we generate a corresponding energy eigenstate by twirling operations, which evolve the system under the Hamiltonian controlled by the ancilla qubits.

Abstract Quantum Key Distribution (QKD) is increasingly pivotal in securing communication channels against the looming threats posed by quantum computing. However, existing QKD protocols encounter challenges related to efficiency and transmission capabilities. In response, this research investigates the integration of metamaterials into QKD systems, aiming to fortify security and enhance practicality. In the current landscape of quantum communication, where the vulnerability of classical encryption methods is magnified by rapid advancements in quantum computing, finding innovative solutions is imperative. This study is motivated by the need to strengthen the security and viability of QKD protocols to meet the demands of evolving cryptographic threats. By integrating metamaterials, the authors optimise quantum state control, improve signal‐to‐noise ratio (SNR), and enable longer transmission distances. Through mathematical modelling and simulations, the authors demonstrate how metamaterials reduce errors and enhance the robustness of QKD systems. Our findings show significant improvements in transmission efficiency and security, making Metamaterial‐Based Quantum Key Distribution (MQKD) a promising approach for future quantum communication networks. The study not only advances the understanding of the theoretical foundations, but also presents simulated results illustrating the practical effectiveness of MQKD. The exploration of these innovative techniques contributes to the ongoing efforts to secure quantum communication channels.

Abstract The integration of lattice‐based cryptography principles with Quantum Key Distribution (QKD) protocols is explored to enhance security in the context of Internet of Things (IoT) ecosystems. With the advent of quantum computing, traditional cryptographic methods are increasingly susceptible to attacks, necessitating the development of quantum‐resistant approaches. By leveraging the inherent resilience of lattice‐based cryptography, a synergistic fusion with QKD is proposed to establish secure and robust communication channels among IoT devices. Through comprehensive Qiskit simulations and theoretical analysis, the feasibility, security guarantees, and performance implications of this novel hybrid approach are thoroughly investigated. The findings not only demonstrate the efficacy of lattice‐based QKD in mitigating quantum threats, but also highlight its potential to fortify IoT communications against emerging security challenges. Moreover, the authors provide valuable insights into the practical implementation considerations and scalability aspects of this fusion approach. This research contributes to advancing the understanding of quantum‐resistant cryptography for IoT applications and paves the way for further exploration and development in this critical domain.

Abstract 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.