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arXiv 2024年

作者： An, Dong Childs, Andrew M. Lin, Lin Ying, Lexing Beijing International Center for Mathematical Research Peking University China Joint Center for Quantum Information and Computer Science University of Maryland College Park United States Department of Computer Science Institute for Advanced Computer Studies University of Maryland College Park United States Department of Mathematics University of California Berkeley United States Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley United States Challenge Institute for Quantum Computation University of California Berkeley United States Department of Mathematics Stanford University United States Institute for Computational and Mathematical Engineering Stanford University United States

Eigenvalue transformations, which include solving time-dependent differential equations as a special case, have a wide range of applications in scientific and engineering computation. While quantum algorithms for singular value transformations are well studied, eigenvalue transformations are distinct, especially for non-normal matrices. We propose an efficient quantum algorithm for performing a class of eigenvalue transformations that can be expressed as a certain type of matrix Laplace transformation. This allows us to significantly extend the recently developed linear combination of Hamiltonian simulation (LCHS) method [An, Liu, Lin, Phys. Rev. Lett. 131, 150603, 2023;An, Childs, Lin, arXiv:2312.03916] to represent a wider class of eigenvalue transformations, such as powers of the matrix inverse, A-k, and the exponential of the matrix inverse, e-A-1. The latter can be interpreted as the solution of a mass-matrix differential equation of the form Au′(t) = -u(t). We demonstrate that our eigenvalue transformation approach can solve this problem without explicitly inverting A, reducing the computational complexity. Copyright © 2024, The Authors. All rights reserved.

关键词： Hamiltonians

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Comment on "Amplified emission and lasing in photonic time crystals"

arXiv

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arXiv 2022年

作者： Park, Jagang Park, Hee Chul Lee, Kyungmin Shin, Jonghwa Ryu, Jung-Wan Jeon, Wonju Park, Namkyoo Min, Bumki Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Daejeon34126 Korea Republic of Department of Physics Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Material Sciences and Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of

Lyubarov et al. (Research Articles, 22 July 2022, p. 425) claim that the spontaneous emission rate of an atom vanishes at the momentum gap edges of photonic Floquet media. We show that their theoretical prediction is based on assumptions that result in misleading interpretations on the spontaneous emission rate in photonic Floquet media. © 2022, CC BY.

关键词： Spontaneous emission

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Spectral Efficiency Maximization for Probabilistic Semantic Communication with Rate Splitting

Spectral Efficiency Maximization for Probabilistic Semantic ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Zhouxiang Zhao Zhaohui Yang Mingzhe Chen Xu Gan Chongwen Huang Yao Sun Qianqian Yang Wei Xu Zhaoyang Zhang College of Information Science and Electronic Engineering Zhejiang University Hangzhou China Zhejiang Provincial Key Laboratory of Info. Proc. Commun. & Netw. (IPCAN) Hangzhou China Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA James Watt School of Engineering University of Glasgow Glasgow UK National Mobile Communications Research Laboratory Southeast University Nanjing China

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

In this paper, the problem of joint transmission and computation resource allocation for probabilistic semantic communication (PSC) network with rate splitting multiple access (RSMA) is investigated. In the considered model, the base station (BS) needs to transmit a large amount of data, which is represented by substantial knowledge graphs, to multiple users. Due to limited communication resource, the BS needs to utilize semantic communication techniques to compress the large-sized data. In this paper, the semantic communication is enabled by shared probability graphs between the BS and users. The process of semantic compression requires computation power at the BS, which has an impact on limited power budget. Therefore, it is necessary to balance the power between transmission and computation. Based on the probability graph, the semantic rate related to semantic compression ratio is first theoretically formulated. Then, the problem is formulated as an optimization problem with the aim of maximizing the sum semantic rate of all users under total power, semantic compression ratio, and rate allocation constraints. To tackle this problem, an iterative algorithm is accordingly proposed to obtain a suboptimal solution. Numerical results validate the effectiveness of the proposed scheme.

关键词： Vehicular and wireless technologies Spectral efficiency Computational modeling Semantics Knowledge graphs Probabilistic logic Numerical models

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Filling the Missing: Exploring Generative AI for Enhanced Federated Learning over Heterogeneous Mobile Edge Devices

arXiv

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arXiv 2023年

作者： Li, Peichun Zhang, Hanwen Wu, Yuan Qian, Liping Yu, Rong Niyato, Dusit Shen, Xuemin The State Key Laboratory of Internet of Things for Smart City University of Macau China Department of Computer and Information Science University of Macau China College of Information Engineering Zhejiang University of Technology Hangzhou310023 China School of Automation Guangdong University of Technology Guangzhou China Guangdong Key Laboratory of IoT Information Technology Guangzhou China The School of Computer Science and Engineering Nanyang Technological University Block N4-02a-32 Nanyang Avenue Singapore Singapore The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Distributed Artificial Intelligence (AI) model training over mobile edge networks encounters significant challenges due to the data and resource heterogeneity of edge devices. The former hampers the convergence rate of the global model, while the latter diminishes the devices’ resource utilization efficiency. In this paper, we propose a generative AI-empowered federated learning to address these challenges by leveraging the idea of FIlling the MIssing (FIMI) portion of local data. Specifically, FIMI can be considered as a resource-aware data augmentation method that effectively mitigates the data heterogeneity while ensuring efficient FL training. We first quantify the relationship between the training data amount and the learning performance. We then study the FIMI optimization problem with the objective of minimizing the device-side overall energy consumption subject to required learning performance constraints. The decomposition-based analysis and the cross-entropy searching method are leveraged to derive the solution, where each device is assigned suitable AI-synthesized data and resource utilization policy. Experiment results demonstrate that FIMI can save up to 50% of the device-side energy to achieve the target global test accuracy in comparison with the existing methods. Meanwhile, FIMI can significantly enhance the converged global accuracy under the non-independently-and-identically distribution (non-IID) data. © 2023, CC BY.

关键词： Energy utilization

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Hyperedge overlap drives synchronizability of systems with higher-order interactions

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Physical Review E 2025年第3期111卷 034302-034302页

作者： Santiago Lamata-Otín Federico Malizia Vito Latora Mattia Frasca Jesús Gómez-Gardeñes Department of Condensed Matter Physics University of Zaragoza 50009 Zaragoza Spain GOTHAM Laboratory Institute of Biocomputation and Physics of Complex Systems (BIFI) University of Zaragoza 50018 Zaragoza Spain Department of Physics and Astronomy University of Catania 95125 Catania Italy School of Mathematical Sciences Queen Mary University of London London E1 4NS United Kingdom Complexity Science Hub Vienna A-1080 Vienna Austria Department of Electrical Electronics and Computer Science Engineering University of Catania 95125 Catania Italy

The microscopic organization of dynamical systems coupled via higher-order interactions plays a pivotal role in understanding their collective behavior. In this paper, we introduce a framework for systematically investigating the impact of the interaction structure on dynamical processes. Specifically, we develop an hyperedge overlap matrix whose elements characterize the two main aspects of the microscopic organization of higher-order interactions: the inter-order hyperedge overlap (nondiagonal matrix elements) and the intra-order hyperedge overlap (encapsulated in the diagonal elements). In this way, the first set of terms quantifies the extent of superposition of nodes among hyperedges of different orders, while the second focuses on the number of nodes in common between hyperedges of the same order. Our findings indicate that large values of both types of hyperedge overlap hinder synchronization stability, and that the larger is the order of interactions involved, the more important is their role. Our findings also indicate that the two types of overlap have qualitatively distinct effects on the dynamics of coupled chaotic oscillators. In particular, large values of intra-order hyperedge overlap hamper synchronization by favoring the presence of disconnected sets of hyperedges, while large values of inter-order hyperedge overlap hinder synchronization by increasing the number of shared nodes between groups converging on different trajectories, without necessarily causing disconnected sets of hyperedges.

关键词： Synchronization

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Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna Systems

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2024年

作者： Liu, Zhan Liao, Zhiyuan Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. Hunan University of Humanities Science and Technology School of Information Loudi417000 China Nanchang University School of Information Engineering Nanchang330031 China Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction Nanchang330031 China South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAS), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. Specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (QoS) requirements of CUs and DUs and the maximum power constraints of RAUs, CUs, and DUs. In addition, we propose a novel spectrum sharing strategy that allows each subcarrier to be assigned to multiple CUs and/or multiple D2D pairs (DPs) for flexibility. To solve the formulated non-convex optimization problem, we first employ fractional programming to transform the objective function in the optimization problem from the fractional form into the equivalent subtractive form. Then, an efficient iterative resource allocation algorithm is proposed, which needs to solve an inner problem in each iteration. After relaxing the variables and introducing penalty factors, the non-convex inner problem is transformed into a convex problem through the successive convex approximation (SCA) method and solved by iterative algorithm. Simulation results demonstrate that the proposed algorithm can considerably improve the system EE compared to other benchmark schemes. Furthermore, the proposed spectrum sharing strategy is superior to the existing sharing strategies. © 2017 IEEE.

关键词： Convex optimization

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Fault Analysis of Microgrids with Inverter Interfaced Resources in Grid-Connected and Islanded Modes

Fault Analysis of Microgrids with Inverter Interfaced Resour...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Jigyesh Sharma Kushan Tharuka Lulbadda Anindita Golder Tarlochan Sidhu Sheldon S. Williamson Department of Electrical and Computer Engineering Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Smart Transportation Electrification and Energy Research (STEER) Group Ontario Tech University Oshawa ON Canada

The increasing penetration of inverter-based generation such as solar, wind and battery energy storage systems (BESS) has an impact on the fault currents in a microgrid. Also, if the microgrid is grid-connected or islanded affects the fault current. As such, it is important to conduct fault analysis of microgrids in grid-connected and islanded modes with different penetration levels of inverter-based generation sources to understand the impact of increasing levels of renewable energy on the fault currents. Different types of faults in a microgrid with inverter-based resources are simulated and the results are discussed and analyzed in this paper.

关键词： Wind energy generation Industrial electronics Renewable energy sources Wind energy Microgrids Inverters Batteries

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EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Towards Large-Scale EEG Model

arXiv

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arXiv 2024年

作者： Qin, Chengxuan Yang, Rui You, Wenlong Chen, Zhige Zhu, Longsheng Huang, Mengjie Wang, Zidong School of Advanced Technology Xi’an Jiaotong-Liverpool University Suzhou215123 China School of Electrical Engineering Electronics and Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom Department of Computing The Hong Kong Polytechnic University Hong Kong Design School Xi’an Jiaotong-Liverpool University Suzhou215123 China Department of Computer Science Brunel University London Uxbridge MiddlesexUB8 3PH United Kingdom

The increasing number of dispersed EEG dataset publications and the advancement of large-scale Electroencephalogram (EEG) models have increased the demand for practical tools to manage diverse EEG datasets. However, the inherent complexity of EEG data, characterized by variability in content data, metadata, and data formats, poses challenges for integrating multiple datasets and conducting large-scale EEG model research. To tackle the challenges, this paper introduces EEGUnity, an open-source tool that incorporates modules of "EEG Parser", "Correction", "Batch Processing", and "Large Language Model Boost". Leveraging the functionality of such modules, EEGUnity facilitates the efficient management of multiple EEG datasets, such as intelligent data structure inference, data cleaning, and data unification. In addition, the capabilities of EEGUnity ensure high data quality and consistency, providing a reliable foundation for large-scale EEG data research. EEGUnity is evaluated across 25 EEG datasets from different sources, offering several typical batch processing workflows. The results demonstrate the high performance and flexibility of EEGUnity in parsing and data processing. The project code is publicly available at ***/Baizhige/EEGUnity. Copyright © 2024, The Authors. All rights reserved.

关键词： Data integration

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2D Ge₂Se₂P₄ Monolayer: A Versatile Photocatalyst for Sustainable Water Splitting

引用

Journal of Physical Chemistry C 2024年第10期128卷 4245-4257页

作者： Vu, Tuan V. Hieu, Nguyen N. Vo, Dat D. Kartamyshev, A.I. Tong, Hien D. Trinh, Thuat T. Khuong Dien, Vo Haman, Zakaryae Dey, Poulumi Khossossi, Nabil Laboratory for Computational Physics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City 70000 Viet Nam Faculty of Mechanical─Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City 70000 Viet Nam Institute of Research and Development Duy Tan University Da Nang 550000 Viet Nam Faculty of Natural Sciences Duy Tan University Da Nang 550000 Viet Nam Faculty of Engineering Vietnamese-German University Binh Duong 820000 Viet Nam Porelab Department of Chemistry Norwegian University of Science and Technology Høgskoleringen 5 Trondheim 7491 Norway Department of Physics National Cheng Kung University 1 University Road Tainan 70101 Taiwan Laboratoire de Physique des Matèriaux et Modélisations des Systèmes LP2MS Faculty of Sciences Department of Physics Moulay Ismail University Meknes 50050 Morocco Department of Materials Science and Engineering Faculty of Mechanical Engineering Delft University of Technology Mekelweg 2 Delft 2628 CD Netherlands

This study aims to identify photo-/electrocatalysts that can enhance the oxygen evolution reaction (OER), hydrogen evolution reaction (HER), and oxygen reduction reaction (ORR), which are of utmost importance in electro-/photochemical energy systems, such as solar energy, fuel cells, water electrolyzers, or metal-air batteries. Our study focused on investigating the 2D Ge₂Se₂P₄ monolayer and found that it exhibits a bifunctional photocatalyst with a very high solar-to-hydrogen efficiency. The two-dimensional (2D) Ge₂Se₂P₄ monolayer has superior HER activity compared to that of most 2D materials, and it also outperforms the reference catalysts IrO₂(110) and Pt(111) in terms of low overpotential values for ORR and OER mechanisms. Such superior catalytic performance in the 2D Ge₂Se₂P₄ monolayer can be attributed to its electron states, charge transfer process, and suitable band alignments referring to normal hydrogen electrodes. Overall, the study suggests that the Ge₂Se₂P₄ monolayer could be an excellent bifunctional catalyst for advancing photo-/electrochemical energy systems. © 2024 American Chemical Society.

关键词： Energy Evolution reactions Free energy Hydrogen Monolayers

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A Dual-Objective Bandit-Based Opportunistic Band Selection Strategy for Hybrid-Band V2X Metaverse Content Update

A Dual-Objective Bandit-Based Opportunistic Band Selection S...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Sherief Hashima Zubair Md Fadlullah Mostafa M. Fouda Kohei Hatano Eiji Takimoto Mohsen Guizani Computational Learning Theory Team RIKEN-AIP Fukuoka Japan Department of Computer Science Western University London ON Canada Department of Electrical and Computer Engineering Idaho State University Pocatello ID USA Center for Advanced Energy Studies (CAES) Idaho Falls ID USA Department of Informatics Kyushu University Fukuoka Japan Machine Learning Department Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI) UAE

As vehicular communication networks embrace metaverse beyond 5G/6G systems, the rich content update via the least interfered subchannel of the optimal frequency band in a hybrid band vehicle to everything (V2X) setting emerges as a challenging optimization problem. We model this problem as a tradeoff between multi-band VR/AR devices attempting to perform metaverse scenes and environmental updates to metaverse roadside units (MRSUs) while minimizing energy consumption. Due to the computational hardness of this optimization, we formulate an opportunistic band selection problem using a multi-armed bandit (MAB) that provides a good quality solution in real-time without computationally burdening the already stretched augmented/virtual reality (AR/VR) units acting as transmitting nodes. The opportunistic use of scheduling rich content updates at traffic signals and stand-still scenarios maps well with the formulated bandit problem. We propose a Dual-Objective Minimax Optimal Stochastic Strategy (DOMOSS) as a natural solution to this problem. Through extensive computer-based simulations, we demonstrate the effectiveness of our proposal in contrast to baselines and comparable solutions. We also verify the quality of our solution and the convergence of the proposed strategy.

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