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Heralded optical entanglement distribution via lossy quantum channels: a comparative study

Optics Express 2025年第6期33卷 12459-12474页

作者： Zo, Wan Chin, Seungbeom Kim, Yong-Su Seoul02792 Korea Republic of Department of Physics and Astronomy Seoul National University Seoul08826 Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Okinawa Institute of Science and Technology Graduate University Okinawa904-0495 Japan Division of Quantum Information Korea University of Science and Technology KIST School Seoul02792 Korea Republic of

Quantum entanglement serves as a foundational resource for various quantum technologies. In optical systems, entanglement distribution relies on the indistinguishability and spatial overlap of photons. Heralded schemes play a crucial role in ensuring the reliability of entanglement generation by detecting ancillary photons to signal the creation of desired entangled states. However, photon losses in quantum channels remain a significant challenge, limiting the distance and capacity of entanglement distributions. This study suggests three heralded schemes for distributing multipartite Greenberger-Horne-Zeilinger (GHZ) states via lossy quantum channels. These schemes differ both qualitatively in their network architecture (centralized or decentralized) and photon source requirements (Bell states or single-photons), and quantitatively in their success probabilities and heralding efficiency. Through comprehensive analysis incorporating both practical implementation considerations and theoretical performance metrics, we find that each scheme offers distinct advantages depending on the number of parties, channel distance, and security requirements. The decentralized scheme proves particularly advantageous for networks requiring balanced information distribution, while centralized schemes may offer better performance for smaller networks. This analysis provides insights into designing resilient heralded circuits for quantum information processing over lossy channels, considering both architectural constraints and performance requirements. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Quantum channel

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Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect

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光：科学与应用（英文版） 2025年第2期14卷 307-332页

作者： Zhiyuan Liu Haicheng Cao Xiao Tang Tingang Liu Yi Lu Zixian Jiang Na Xiao Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering ProgramCEMSE DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as AR/***,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size *** seriously impedes the development and application of *** this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical ***,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall ***,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED *** believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficient InGaN micro-LEDs.

关键词： technologies micro-led advanced ingan effect fabrication mitigate sidewall

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Graph-based design of irregular metamaterials

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International Journal of Mechanical sciences 2025年 295卷

作者： Karimi Mahabadi, Rayehe Chen, Zhi Ogren, Alexander C. Zhang, Han Daraio, Chiara Rudin, Cynthia Brinson, L. Catherine Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States Departments of Computer Science and Electrical and Computer Engineering Duke University DurhamNC United States Division of Engineering and Applied Science California Institute of Technology PasadenaCA United States

In the field of metamaterial research, irregular structures offer a novel and less conventional approach compared to traditional periodic designs. Designing irregular metamaterials is challenging when it comes to ensuring interconnectivity, which is essential for manufacturability. This study introduces an innovative framework for generating irregular metamaterials using graph algorithms, ensuring connectivity and adaptability across various base shapes, including cylinders, triangles, pyramids, and cubes. By employing graph algorithms, our framework enhances the intuitiveness and efficiency of design representation and manipulation, streamlining the design process. The framework generates families of designs that exhibit a wide range of property magnitudes that can be adjusted intuitively by modifying the input parameters. The rapid design process allows many designs to be generated, offering the user a multitude of solutions around the target property range. The designs can be effectively implemented in various fields and subjected to diverse analytical studies, including static, dynamic, and eigenfrequency assessments. We illustrate computational results for two key properties (stiffness and acoustic impedance), showcasing the method's effectiveness through examples ranging from rod-based to cube-based designs. The framework not only advances metamaterial research but also creates new opportunities for innovation in fields requiring customized material properties. © 2025

关键词： Acoustic impedance

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VMGuard: Reputation-Based Incentive Mechanism for Poisoning Attack Detection in Vehicular Metaverse

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IEEE Transactions on Vehicular Technology 2025年

作者： Lotfi, Ismail Qaraqe, Marwa Ghrayeb, Ali Niyato, Dusit Hamad Bin Khalifa University Division of Information and Computing Technology College of Science and Engineering Doha Qatar Nanyang Technological University School of Computer Science and Engineering Singapore Singapore

The vehicular Metaverse represents an emerging paradigm that merges vehicular communications with virtual environments, integrating real-world data to enhance in-vehicle services. However, this integration faces critical security challenges, particularly in the data collection layer where malicious sensing IoT (SIoT) devices can compromise service quality through data poisoning attacks. The security aspects of the Metaverse services should be well addressed both when creating the digital twins of the physical systems and when delivering the virtual service to the vehicular Metaverse users (VMUs). This paper introduces vehicular Metaverse guard (VMGuard), a novel four-layer security framework that protects vehicular Metaverse systems from data poisoning attacks. Specifically, when the virtual service providers (VSPs) collect data about physical environment through SIoT devices in the field, the delivered content might be tampered. Malicious SIoT devices with moral hazard might have private incentives to provide poisoned data to the VSP to degrade the service quality (QoS) and user experience (QoE) of the VMUs. The proposed framework implements a reputation-based incentive mechanism that leverages user feedback and subjective logic modeling to assess the trustworthiness of participating SIoT devices. More precisely, the framework entails the use of reputation scores assigned to participating SIoT devices based on their historical engagements with the VSPs. These scores are calculated from feedback provided by the VMUs to the VSPs regarding the content they receive and are managed utilizing a subjective logic model. Ultimately, we validate our proposed model using comprehensive simulations. Our key findings indicate that our mechanism effectively prevents the initiation of poisoning attacks by malicious SIoT devices. Additionally, our system ensures that reliable SIoT devices, previously misclassified, are not barred from participating in future rounds of the market. T

关键词： Deep reinforcement learning

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Exploring the Synergy: A Review of Dual-Functional Radar Communication Systems

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IEEE Aerospace and Electronic Systems Magazine 2025年

作者： Hanif, Ali Ahmed, Sajid Alouini, Mohamed-Slim Al-Naffouri, Tareq Y. King Abdullah University of Science and Technology Department of Electrical and Computer Engineering CEMSE Division Thuwal23955 Saudi Arabia

This review paper examines the concept and advancements in the evolving landscape of Dual-functional Radar Communication (DFRC) systems. Traditionally, radar and communication systems have functioned independently, but current research is actively investigating the integration of these functionalities into a unified platform. The paper discusses the motivations behind the development of DFRC systems, the challenges involved, and the potential benefits they offer. A discussion on the performance bounds for DFRC systems is also presented. The paper provides a comprehensive review of the state-of-the-art research on DFRC systems covering various design aspects, resource allocation strategies, and future research directions. Additionally, we explore potential application scenarios for these joint communication and sensing systems, offering a comprehensive perspective on the multifaceted landscape of DFRC technology. This paper also presents a tutorial-style signal model for integrated sensing and communication tailored for newcomers to the field. © 2025 IEEE. All rights reserved.

关键词： Resource allocation

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DFRC Signaling Strategies based on MIMO Beampattern Invariance

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IEEE Transactions on Communications 2025年

作者： Mazahir, Sana Ahmed, Sajid Alouini, Mohamed-Slim King Abdullah University of Science and Technology CEMSE Division Department of Electrical and Computer Engineering Thuwal23955 Saudi Arabia

The Dual-function radar communication (DFRC) design aims to exploit the tractability and reusability of both radar and communication systems' components, parameters, and spectrum to achieve an integrated system. In this work, we propose a novel DFRC signal design by leveraging the phenomenon of the MIMO beampattern invariance, which was comprehensively explored in our previous work [1]. It is demonstrated that the flexibility afforded by this beampattern invariance can be used to construct an integrated waveform while maintaining the required beam. A beampattern-preserving unitary transformation of the MIMO weight matrix is proposed to realize a desired information-bearing symbol at the communication receiver. The proposed method has the following promising features: 1) low-complexity, closed-form solution for the transmitted signals;2) flexibility of modulation scheme;3) independence from the type of orthonormal MIMO waveforms;4) independence from the beampattern design;5) adaptability for multi-target and multi-user scenarios. Using this generic signal design method, a number of modulation schemes are implemented. Furthermore, the impact of this operation on the estimation accuracy of the target parameters is analyzed by computing their respective Cramer-Rao Lower Bounds (CRLBs). Simulation results show that modulation schemes yielding a range of symbol error rate (SER) performances can be implemented while keeping the radar parameter estimation unaffected. © 2025 IEEE.

关键词： Cramer-Rao bounds

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SSB-Based Multi-Target Detection and Joint Velocity, Angle, and Range Estimation in 5G-NR

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IEEE Communications Letters 2025年

作者： Awad, Yousef Celik, Abdulkadir Eltawil, Ahmed King Abdullah University of Science and Technology Computer Electrical and Mathematical Sciences and Engineering Division Thuwal23955 Saudi Arabia

This work aims to leverage the existing fifth generation (5G) new radio (NR) synchronization signal (SS) burst for network-side integrated sensing and communications (ISAC). A novel density-based clustering of applications with noise (DBSCAN)-based multi target detection algorithm is proposed. Furthermore, utilizing the beam sweeping nature of the SS burst, joint velocity, angle, and range (JVAR) estimation algorithms are proposed. Simulation results show that the proposed detection algorithm can reach an overall average detection accuracy of around 0.98 for different number of targets scenarios. On the other hand, the JVAR estimation accuracy are dependent on the individual radar resolution of velocity, angle and range. © 2025 IEEE.

关键词： Orthogonal frequency division multiplexing

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A Finite Element Technique for Approximately Solving for the Electromagnetic Field Within a Cavity Resonator 3rd

A Finite Element Technique for Approximately Solving for t...

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3rd International Conference on Computational Electronics for Wireless Communications, ICCWC 2023

作者： Vaish, Arti Parthasarathy, Harish Dua, Rakhi Department of Computer Science and Engineering School of Engineering and Technology O P Jindal University CG Raigarh Punjipathra India Electronics and Communication Division Netaji Subhas University of Technology Dwarka New Delhi India ECE Department KR Manglam University Gurugram India

ISBN: (纸本)9789819719426

This paper develops a four space-time dimensional finite element approach for approximately calculating the electromagnetic and Dirac fields within a 3-D cavity resonator taking into account the interaction between the two fields. The idea is to partition the four-dimensional space-time region consisting of the 3-D cavity and the finite time duration over which the fields are to be determined into four-dimensional simplices. Each simplex is defined by five vertex points in four-dimensional space-time and the fields within each such simplex are expressed as affine linear functions of the four simplex coordinates so that the values of the field at the vertices of the simplex coincides with the field value at that vertex. We then substitute these affine linear functions into the action functional of the electromagnetic field interacting with the Dirac field thereby yielding a quadratic function of the simplex vertex field values corresponding to the free field action plus cubic function of the vertex fields corresponding to the interaction action between the Dirac current and the electromagnetic field. By summing up this action over all the simplices into which we have partitioned the space-time region, we obtain a quadratic-cubic function of the field values at all the vertices of the different simplices. The problem of approximately calculating the fields within the cavity then amounts to minimizing this function of a finite number of complex variables corresponding to the field values at the vertices of the simplices. This optimization can be carried out using for example a gradient search algorithm or using perturbation theory for obtaining solutions to a system of nonlinear algebraic equations when the nonlinearity is small. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Perturbation techniques

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Early-Stage Detection of Colorectal Cancer Using Image Classification

Early-Stage Detection of Colorectal Cancer Using Image Class...

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Sentiment Analysis and Deep Learning (ICSADL), International Conference on

作者： Ashlin Santhosh A M Anusha Bamini M Rajeswari D Brindha R Chitra S Stewart Kirubakaran Division of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India

ISBN: (数字)9798331523923

ISBN: (纸本)9798331523930

Early detection of colorectal cancer is important as it is one of the most common and deadliest types of cancer worldwide. This project proposes an image classification model based on deep learning architecture that could detect colorectal cancer in its preliminary stages by using an EfficientNetB0. By using the Colorectal Cancer Whole Slide Images (WSI) dataset, a classification model using the WSI dataset to classify tissue samples into six distinct categories of varying grades of cancerous growths and normal. In this model, transfer learning is included to maintain computational efficiency while enhancing accuracy. A user interface with Streamlit, which has real-time image upload, analysis, and prediction display, was also developed. The predictions come with confidence scores, and the Interface also provides educational content for each cancer stage to help raise awareness and prevent the disease. Applications with potential for medical diagnosis and as an educational tool for early detection of colorectal cancer are possible for this system.

关键词： Deep learning Analytical models Adaptation models Computational modeling Transfer learning Colorectal cancer Streaming media Predictive models User interfaces Image classification

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An Enhancement of Object Detection Using YOLO V8 and Mobile Net in Challenging Conditions

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SN computer science 2025年第4期6卷 1-20页

作者： Pasupuleti, Shailaja Ramalakshmi, K. Gunasekaran, Hemalatha Arokiaraj, Rex Macedo Debnath, Saswati Jebaseeli, T. Jemima Department of Computer Science and Engineering Alliance University Karnataka Anekal Bangalore India AU-Centre of Excellence Department of Computer Vision Alliance University Karnataka Anekal Bangalore India College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Information Technology College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman Department of Computer Science and Engineering Alliance University Karnataka Bangalore India Division of Artificial Intelligence and Machine Learning Karunya Institute of Technology and Sciences Coimbatore India

Autonomous drones and deep learning neural networks are becoming popular tools to revolutionize aircraft operations by partially automating visual inspection processes in aircraft maintenance. The research aims to provide a trustworthy method for locating and classifying surface flaws on aircraft, such as dents, fractures, corrosion, and a few other anomalies. To assess the model performance with and without a lightweight network integration, the implementation merges YOLOv8 and Mobile Net architectures, using dropout regularization and data augmentation approaches. To guarantee the model's performance in low-light situations, the dataset has been carefully selected to contain images replicating such settings. Annotation, environment setup, model training, and online dataset scraping are all covered by the thorough technique. A web-scraped dataset is used to train and validate two popular semantic segmentation algorithms, YOLOv8 and Mobile Net, which show enough performance for segmenting and grading aircraft surface problems in practical settings. The results show that precision and recall values are improved using a hybrid technique that ensembles trained Mobile Net and YOLOv8 models. Using COCO metrics, in the proposed approach an assessment of Ensemble WBF, Mobile Net-YOLO, and YOLOv8 outcomes on test and validation sets, guaranteed reliable object recognition and classification abilities. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： Aircraft Classification Mobile-Net Object detection Weighted Box Fusion YOLOv8

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