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Quantum qubit-optical cavity node: Effects of the temperature and coupling strengths on the cavity Fock-state distribution occupation probability and entropy of the subsystems using Dicke model

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Results in Physics 2025年 72卷

作者： Barhoumi, Mohamed Bassoli, Riccardo Fitzek, Frank H.P. Laboratory of Condensed Matter and Nanosciences (LMCN) Department of Physics Faculty of Sciences of Monastir University of Monastir Environment Street Monastir 5019 Tunisia Institut Supérieur d'Informatique et de Mathématiques de Monastir (ISIMM) University of Monastir Avenue de la Corniche Monastir 5000 Tunisia Deutsche Telekom Chair of Communication Networks Institute of Communication Technology Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany Centre for Tactile Internet with Human-in-the-Loop (CeTI) Cluster of Excellence Dresden Germany Quantum Communication Networks (QCNets) research group Institute of Communication Technology Faculty of Electrical and Computer Engineering Technische Universität Dresden Dresden Germany

One of the most attractive systems for scalable quantum processing is the trapped atom in the optical cavity, which is easily manipulable with lasers. The qubit cavity system represents an attractive structure for quantum optics, with possibilities for applications in quantum detecting, quantum computation, and quantum communication. In addition, the investigation of the cavity-atom system under temperature is a fundamental concept in quantum optics and quantum information science. Here we continue in this quantum way, investigating different qubit(s)-cavity systems (where we increase the numbers of the qubit inside the optical cavity from one to four). Using the Dicke model, we calculate the probability of occupation of the ground state of the cavity 〈aˆ^†aˆ〉 and the expectation values 〈J_z〉 for each system. We find that these probabilities increase as the coupling strength C_s increases. This leads to reaching the ultra-strong coupling regime, which depends on the number of qubits. To describe the quantum state, we examine the cavity Wigner function WF as a function of the coupling strength C_s. Under the same parameters (e.g. C_s and the dissipation rates), we find that the separation of the quantum state in the WFs representation is different from one system to another. Furthermore, since understanding these kinds of systems is very important in order to improve the quantum network system, we study the entropy S of the subsystems (such as S of qubit) in each system. Also, we move beyond by studying the effect of the temperature on the Fock-state distribution occupation probability and entropy of the subsystems. Our results present another step to understanding the qubit(s)-cavity interaction to improve the performance of future quantum networks based on this system. Where the interplay between temperature, coupling strengths, and the Fock-state occupation probabilities contributes significantly to the understandi

关键词： Cavity Dicke model Quantum communication networks Quantum nodes Quantum state Qubit Qubit–cavity system Temperature

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Spatial Computing: Concept, Applications, Challenges and Future Directions

arXiv

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arXiv 2024年

作者： Yenduri, Gokul Ramalingam, M. Maddikunta, Praveen Kumar Reddy Gadekallu, Thippa Reddy Jhaveri, Rutvij H. Bandi, Ajay Chen, Junxin Wang, Wei Shirawalmath, Adarsh Arunkumar Ravishankar, Raghav Wang, Weizheng School of Computer Science and Engineering VIT-AP University Andhra Pradesh Amaravati522237 India School of Computer Science Engineering and Information Systems Vellore Institute of Technology TamilNadu 632014 India Zhongda Group Haiyan County Zhejiang Province Jiaxing City314312 China College of Information Science and Engineering Jiaxing University Jiaxing314001 China Division of Research and Development Lovely Professional University Phagwara India Department of Computer Science and Engineering School of Technology Pandit Deendayal Energy University Gandhinagar India School of Computer Science and Information Systems Northwest Missouri State University 800 University Dr MaryvilleMO64468 United States School of Software Dalian University of Technology Dalian116621 China Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University Guangdong Shenzhen518172 China School of Medical Technology Beijing Institute of Technology Beijing100081 China School of Computer Science and Engineering Vellore Institute of Technology TamilNadu 632014 India Department of Computer Science City University of Hong Kong Hong Kong

Spatial computing is a technological advancement that facilitates the seamless integration of devices into the physical environment, resulting in a more natural and intuitive digital world user experience. Spatial computing has the potential to become a significant advancement in the field of computing. From GPS and location-based services to healthcare, spatial computing technologies have influenced and improved our interactions with the digital world. The use of spatial computing in creating interactive digital environments has become increasingly popular and effective. This is explained by its increasing significance among researchers and industrial organisations, which motivated us to conduct this review. This review provides a detailed overview of spatial computing, including its enabling technologies and its impact on various applications. Projects related to spatial computing are also discussed. In this review, we also explored the potential challenges and limitations of spatial computing. Furthermore, we discuss potential solutions and future directions. Overall, this paper aims to provide a comprehensive understanding of spatial computing, its enabling technologies, their impact on various applications, emerging challenges, and potential solutions. © 2024, CC BY.

关键词： Augmented reality

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Deep learning-based instance segmentation for the precise automated quantification of digital breast cancer immunohistochemistry images

arXiv

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arXiv 2023年

作者： Priego-Torres, Blanca Maria Lobato-Delgado, Barbara Atienza-Cuevas, Lidia Sanchez-Morillo, Daniel Biomedical Engineering and Telemedicine Research Group Department of Automation Engineering Electronics and Computer Architecture and Networks School of Engineering University of Cádiz Avda. Universidad de Cádiz 10 Cádiz Puerto Real11510 Spain Hospital Universitario Puerta del Mar Avda Ana de Viya 21 Cádiz11009 Spain Department of Pathology Hospital Universitario Puerta del Mar Avda. Ana de Viya 21 Cádiz11009 Spain

The quantification of biomarkers on immunohistochemistry breast cancer images is essential for defining appropriate therapy for breast cancer patients, as well as for extracting relevant information on disease prognosis. This is an arduous and time-consuming task that may introduce a bias in the results due to intra- and inter-observer variability which could be alleviated by making use of automatic quantification tools. However, this is not a simple processing task given the heterogeneity of breast tumors that results in non-uniformly distributed tumor cells exhibiting different staining colors and intensity, size, shape, and texture, of the nucleus, cytoplasm and membrane. In this research work we demonstrate the feasibility of using a deep learning-based instance segmentation architecture for the automatic quantification of both nuclear and membrane biomarkers applied to IHC-stained slides. We have solved the cumbersome task of training set generation with the design and implementation of a web platform, which has served as a hub for communication and feedback between researchers and pathologists as well as a system for the validation of the automatic image processing models. Through this tool, we have collected annotations over samples of HE, ER and Ki-67 (nuclear biomarkers) and HER2 (membrane biomarker) IHC-stained images. Using the same deep learning network architecture, we have trained two models, so-called nuclei- and membrane-aware segmentation models, which, once successfully validated, have revealed to be a promising method to segment nuclei instances in IHC-stained images. The quantification method proposed in this work has been integrated into the developed web platform and is currently being used as a decision support tool by pathologists. © 2023, CC BY-NC-ND.

关键词： Textures

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基于低成本联邦宽度学习的智能超表面辅助车联网中隐私保护知识共享（英文）

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engineering 2024年第2期 178-189页

作者： Xiaoming Yuan Jiahui Chen Ning Zhang Qiang (John) Ye Changle Li Chunsheng Zhu Xuemin Sherman Shen Qinhuangdao Branch Campus Northeastern University State Key Laboratory of Integrated Services Networks & the Research Institute of Smart Transportation Xidian University Department of Electrical and Computer Engineering University of Windsor Department of Electrical and Software Engineering University of Calgary SUSTech Institute of Future Networks Southern University of Science and Technology Department of Electrical and Computer Engineering University of Waterloo

High-efficiency and low-cost knowledge sharing can improve the decision-making ability of autonomous vehicles by mining knowledge from the Internet of Vehicles(IoVs).However,it is challenging to ensure high efficiency of local data learning models while preventing privacy leakage in a high mobility *** order to protect data privacy and improve data learning efficiency in knowledge sharing,we propose an asynchronous federated broad learning(FBL) framework that integrates broad learning(BL) into federated learning(FL).In FBL,we design a broad fully connected model(BFCM) as a local model for training client *** enhance the wireless channel quality for knowledge sharing and reduce the communication and computation cost of participating clients,we construct a joint resource allocation and reconfigurable intelligent surface(RIS) configuration optimization framework for *** problem is decoupled into two convex *** to improve the resource scheduling efficiency in FBL,a double Davidon-Fletcher-Powell(DDFP) algorithm is presented to solve the time slot allocation and RIS configuration *** on the results of resource scheduling,we design a reward-allocation algorithm based on federated incentive learning(FIL) in FBL to compensate clients for their *** simulation results show that the proposed FBL framework achieves better performa nce than the comparison models in terms of efficiency,accuracy,and cost for knowledge sharing in the IoV.

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Silicon photonics for high-capacity data communications

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Photonics research 2022年第9期10卷 I0002-I0030页

作者： YAOCHENG SHI YONG ZHANG YATING WAN YU YU YUGUANG ZHANG XIAO HU XI XIAO HONGNAN XU LONG ZHANG BINGCHENG PAN Centre for Optical and Electromagnetic Research State Key Laboratory for Modern Optical InstrumentationCollege of Optical Science and EngineeringZhejiang UniversityZijingang CampusHangzhou 310058China State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic EngineeringShanghai Jiao Tong UniversityShanghai 200240China Institute for Energy Efficiency University of California Santa BarbaraSanta BarbaraCalifornia 93106USA Electrical and Computer Engineering Department King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Wuhan National Laboratory for Optoelectronics&School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China National Information Optoelectronics Innovation Center China Information and Communication Technologies Group Corporation(CICT)Wuhan 430074China State Key Laboratory of Optical Communication Technologies and Networks China Information and Communication Technologies Group Corporation(CICT)Wuhan 430074China Department of Electronic Engineering The Chinese University of Hong KongShatinNew TerritoriesHong KongChina

In recent years,optical modulators,photodetectors,(de)multiplexers,and heterogeneously integrated lasers based on silicon optical platforms have been *** performance of some devices even surpasses the traditional III-V and photonic integrated circuit(PIC)platforms,laying the foundation for large-scale photonic *** photonic technology can overcome the limitations of traditional transceiver technology in high-speed transmission networks to support faster interconnection between data *** this article,we will review recent progress for silicon *** first part gives an overview of recent achievements in silicon *** second part introduces the silicon photonic building blocks,including low-loss waveguides,passive devices,modulators,photodetectors,heterogeneously integrated lasers,and so *** the third part,the recent progress on high-capacity silicon photonic transceivers is *** the fourth part,we give a review of high-capacity silicon photonic networks on chip.

关键词： interconnection passive networks

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An advanced deep neural network for fundus image analysis and enhancing diabetic retinopathy detection

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Healthcare Analytics 2024年 5卷 100303-100303页

作者： Mehedi Shamrat, F M Javed Shakil, Rashiduzzaman Sharmin Hoque ovy, Nazmul Akter, Bonna Ahmed, Md Zunayed Ahmed, Kawsar Bui, Francis M. Moni, Mohammad Ali Department of Computer System and Technology University of Malaya Kuala Lumpur 50603 Malaysia Department of Computer Science and Engineering Daffodil International University Dhaka 1216 Bangladesh Department of Software Engineering Daffodil International University Dhaka 1216 Bangladesh Department of Computer Science and Engineering European University of Bangladesh Dhaka 1216 Bangladesh Department of Electrical and Computer Engineering University of Saskatchewan 57 Campus Drive Saskatoon S7N 5A9 SK Canada Group of Biophotomatiχ Department of Information and Communication Technology Mawlana Bhashani Science and Technology University Santosh Tangail 1902 Bangladesh Health Informatics Research Lab Department of Computer Science and Engineering Daffodil International University Daffodil Smart City (DSC) Birulia Savar Dhaka 1216 Bangladesh School of Health and Rehabilitation Sciences Faculty of Health and Behavioural Sciences The University of Queensland St Lucia 4072 QLD Australia

Diabetic retinopathy (DR) involves retina damage due to diabetes, often leading to blindness. It is diagnosed via color fundus injections, but the manual analysis is cumbersome and error-prone. While computer vision techniques can predict DR stages, they are computationally intensive and struggle with complex data extraction. In this research, our prime objective was to automate the process of DR classification into its various stages using convolutional neural network (CNN) models. We employed the performance of fifteen pre-trained models with our novel proposed diabetic retinopathy network (DRNet13) model. We aimed to discern the most efficient model for accurate diabetic retinopathy (DR) staging based on fundus images from five DR classes. We preprocessed the image using a median filter for noise reduction and Gamma correction for image enhancement. We expanded our dataset from 3662 to 7500 images to create a more generalized training model through various augmentation techniques. We also evaluated multiple evaluation metrics, including accuracy, precision, F1-score, Sensitivity, Specificity, Area under the curve (AUC), Mean Squared Error (MSE), False Positive Rate (FPR), False Negative Rate (FNR), in addition to confusion matrices for an in-depth comparison of the performance of these models. Feature maps were employed to illuminate decision making areas in the DRNet13 model, which achieved a 97 % accuracy rate for DR detection, surpassing other CNN architectures in speed and efficiency. Despite a few misclassifications, the model's capability to identify critical features demonstrates its potential as an impactful diagnostic tool for timely and accurate identification of diabetic retinopathy. © 2024 The Authors

关键词： Classification Convolutional neural network Diabetic retinopathy network Diagnostic analytics Feature map

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Massive MIMO 6

Massive MIMO

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6th IEEE Future networks World Forum, FNWF 2023

作者： Sun, Haijian Ng, Chris Huo, Yiming Hu, Rose Qingyang Wang, Ning Chen, Chi-Ming Vasudevan, Kasturi Yang, Jin Montlouis, Webert Ayanda, Dauda Mishra, Kumar Vijay Tekbiyik, Kursat Hussain, Nasir Sahoo, Harish Kumar Miao, Yang Di, Boya Zhang, Hongliang Demir, Ozlem Tugfe University of Wisconsin Department of Computer Science Whitewater United States Ieee Future Networks Massive Mimo Working Group University of Victoria Canada Utah State University United States Zhengzhou University China AT&T Ieee Iit Kanpur India Verizon Communications Inc. United States Johns Hopkins University United States University of KwaZulu-Natal South Africa United States Ccdc Army Research Laboratory United States Istanbul Technical University Department of Electronics and Communication Engineering Turkey Samsung Electronics America United States Veer Surendra Sai University of Technology India University of Twente Netherlands Peking University China Tobb University of Economics and Technology Turkey

ISBN: (纸本)9798350324587

The use of a large number of antenna elements, known as Massive MIMO, is seen as a key enabling technology in the 5G and Beyond wireless ecosystem. The intelligent use of a multitude of antenna elements unleashes unprecedented flexibility and control on the physical channel of the wireless medium. Through Massive MIMO and other techniques, it is envisioned that the 5G and beyond wireless system will be able to support high throughput, high reliability (low bit-error-rate (BER)), high energy efficiency, low latency, and an internet-scale number of connected devices. Massive MIMO and related technologies will be deployed in the mid-band (sub 6 GHz) for coverage, all the way to mmWave bands to support large channel bandwidths. It is envisioned that Massive MIMO will be deployed in different environments: Frequency Division Duplex (FDD), (Time Division Duplex (TDD), indoor / outdoor, small cell, macro cell, and other heterogeneous networks (HetNet) configurations. Accurate and useful channel estimation remains a challenge in the efficient adoption of Massive MIMO techniques, and different performance-complexity tradeoffs may be supported by different Massive MIMO architectures such as digital, analog, and/or digital/analog hybrid. Carrier frequency offset (CFO), which arises due to the relative motion between the transmitter and receiver, is another important topic. Recently, maximum likelihood (ML) methods of CFO estimation have been proposed, that achieve very low root mean square (RMS) estimation errors, with a large scope for parallel processing and well suited for application with turbo codes. Massive MIMO opens up a whole new dimension of parameters where the wireless applications or other network layers may control or influence the operation and performance of the physical wireless channel. To fully reap the benefits of such flexibility, the latest advances in artificial intelligence (AI) and machine learning (ML) techniques will be leveraged to monitor and optim

关键词： Signal to noise ratio

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Chances and Challenges of ChatGPT and Similar Models for Education in M&S

Chances and Challenges of ChatGPT and Similar Models for Edu...

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Simulation Winter Conference

作者： Andreas Tolk Philip Barry Margaret L. Loper Ghaith Rabadi William T. Scherer Levent Yilmaz Modeling and Analysis Innovation Center The MITRE Corporation Charlottesville VA USA Mission Analysis Group L3Harris Corporation Herndon VA USA Georgia Tech Research Institute Georgia Institute of Technology Atlanta GA USA University of Central Florida School of Modeling Simulation and Training Orlando FL USA Department of Systems and Information Engineering University of Virgina Charlottesville VA USA Samuel Ginn College of Engineering Computer Science and Software Engineering Auburn University Auburn AL USA

This position paper summarizes the inputs of a group of experts from academia and industry presenting their view on chances and challenges of using ChatGPT within Modeling and Simulation education. The experts also address the need to evaluate continuous education as well as education of faculty members to address scholastic challenges and opportunities while meeting the expectation of industry. Generally, the use of ChatGPT is encouraged, but it needs to be embedded into an updated curriculum with more emphasis on validity constraints, systems thinking, and ethics.

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Quantum Enhanced Time Synchronisation for Communication Network

TechRxiv

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TechRxiv 2023年

作者： Nande, Swaraj Shekhar Paul, Marius Senk, Stefan Ulbricht, Marian Bassoli, Riccardo Fitzek, Frank H.P. Boche, Holger Deutsche Telekom Chair of Communication Networks Technische Universität Dresden Dresden Germany Cluster of Excellence Dresden Germany Research Group Technische Universität Dresden Dresden Germany Department of Electrical and Computer Engineering Technische Universität München München Germany Schellingstr. 4 München80799 Germany Cluster of Excellence Ruhr Universität Bochum Bochum Germany

It is essential to establish precise times in future communication networks. Any real-time task’s function depends on the system’s ability to synchronise time. Time synchronisation is critical in the current communication network and must be maintained to transmit data packets . The functionality of 6G, the Tactile Internet, Time-Sensitive Networking, and ultra-reliable low-latency communications is highly susceptible to time synchronisation. We investigated the idea of employing time synchronisation across different communication network nodes. The current state-of-the-art employs network protocols like Precision-Time Protocol for synchronising clocks across different nodes. These network protocols are not robust and can generate jitters in data transmission. In this paper, we suggested synchronising the time of the node clocks at three different places using quantum technology. Notably, the oscillation frequencies of each qubit (or oscillator) located at these nodes can be synchronised using the quantum synchronisation technique. This set of three oscillators will work as a single clock and will be the master clock of the network . We propose distributing precise time and frequency standards using quantum synchronisation on node clocks. We can synchronise the three qubits (each placed at one node) to oscillate at an identical frequency by applying an external field of a wavelength of 813.32 nm. We analysed our model for different coupling constants and dissipation rates to provide an analysis of the behaviour of the amount of synchronisation in different experimental configurations. The optimal accuracy for our system is 1.6 × 1015 signals per second. Further, we used the Allan deviation to examine the stability of our system for various noise strengths. © 2023, CC BY.

关键词： Synchronization

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Sowmark: Neural networks Copyright Protection Based on Structural Orthogonal Watermarking

SSRN

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SSRN 2024年

作者： Chen, Xianyi Hui, Mi Xu, Huiguang He, Junjie Engineering Research Center of Digital Forensics Ministry of Education Nanjing University of Information Science and Technology No.219 Ningliu Road Pukou District Nanjing210044 China School of Computer Science Nanjing University of Information Science and Technology No.219 Ningliu Road Pukou District Nanjing210044 China School of Software Nanjing University of Information Science and Technology No.219 Ningliu Road Pukou District Nanjing210044 China NARI Group Corporation State Grid Electric Power Research Institute Nanjing211106 China

A well-trained deep learning model usually consumes a lot of time and computational resources. However, it is vulnerable to infringement as a digital achievement once published. Recently, many impressive works have emerged for deep model copyright protection. They primarily embed watermarks by modifying model parameters or training samples, which can easily lead to model performance degradation. To this end, we propose a new structure-based DNN orthogonal watermarking method, in which the output features of the orthogonal layer are restricted to be parallel or orthogonal to each other by imposing forward constraint rules. It improves the correlation between the watermark and the model parameters, which improves the feature diversity and enables the model's watermark to effectively resist parameter-based attacks, thus improving the overall performance of the model. Extensive experiments have demonstrated that, the proposed scheme has great fidelity and robustness against various watermark removal attacks, such as parameter fine-tuning and model pruning. © 2024, The Authors. All rights reserved.

关键词： Watermarking

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