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arXiv 2022年

作者： Cai, Wenhao Li, Ming Liu, Yang Wu, Qingqing Liu, Qian The School of Information and Communication Engineering Dalian University of Technology Dalian116024 China The State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China Guangdong-Macau Joint Laboratory for Advanced and Intelligent Computing China The School of Computer Science and Technology Dalian University of Technology Dalian116024 China

Intelligent reflecting surface (IRS) has been widely considered as one of the key enabling techniques for future wireless communication networks owing to its ability of dynamically controlling the phase shift of reflected electromagnetic (EM) waves to construct a favorable propagation environment. While IRS only focuses on signal reflection, the recently emerged innovative concept of intelligent omni-surface (IOS) can provide the dual functionality of manipulating reflecting and transmitting signals. Thus, IOS is a new paradigm for achieving ubiquitous wireless communications. In this paper, we consider an IOS-assisted multi-user multi-input single-output (MU-MISO) system where the IOS utilizes its reflective and transmissive properties to enhance the MU-MISO transmission. Both power minimization and sum-rate maximization problems are solved by exploiting the second-order cone programming (SOCP), Riemannian manifold, weighted minimum mean square error (WMMSE), and block coordinate descent (BCD) methods. Simulation results verify the advancements of the IOS for wireless systems and illustrate the significant performance improvement of our proposed joint transmit beamforming, reflecting and transmitting phase-shift, and IOS energy division design algorithms. Compared with conventional IRS, IOS can significantly extend the communication coverage, enhance the strength of received signals, and improve the quality of communication links. © 2022, CC BY.

关键词： Mean square error

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Structure-Preserving Operator Learning: Modeling the Collision Operator of Kinetic Equations

arXiv

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arXiv 2024年

作者： Lee, Jae Yong Schotthöfer, Steffen Xiao, Tianbai Krumscheid, Sebastian Frank, Martin Center for Artificial Intelligence and Natural Sciences Korea Institute for Advanced Study Seoul Korea Republic of Oak Ridge National Laboratory Computer Science and Mathematics Division Oak RidgeTN United States State Key Laboratory of High Temperature Gas Dynamics Centre for Interdisciplinary Research in Fluids Institute of Mechanics Chinese Academy of Sciences Beijing China School of Engineering Science University of Chinese Academy of Sciences Beijing China Karlsruhe Institute of Technology Scientific Computing Center Karlsruhe76131 Germany

This work explores the application of deep operator learning principles to a problem in statistical physics. Specifically, we consider the linear kinetic equation, consisting of a differential advection operator and an integral collision operator, which is a powerful yet expensive mathematical model for interacting particle systems with ample applications, e.g., in radiation transport. We investigate the capabilities of the Deep Operator network (DeepONet) approach to modelling the high dimensional collision operator of the linear kinetic equation. This integral operator has crucial analytical structures that a surrogate model, e.g., a DeepONet, needs to preserve to enable meaningful physical simulation. We propose several DeepONet modifications to encapsulate essential structural properties of this integral operator in a DeepONet model. To be precise, we adapt the architecture of the trunk-net so the DeepONet has the same collision invariants as the theoretical kinetic collision operator, thus preserving conserved quantities, e.g., mass, of the modeled many-particle system. Further, we propose an entropy-inspired data-sampling method tailored to train the modified DeepONet surrogates without requiring an excessive expensive simulation-based data generation. © 2024, CC BY-NC-SA.

关键词： Kinetic energy

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Machine learning prediction of network dynamics with privacy protection

arXiv

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arXiv 2022年

作者： Xia, Xin Su, Yansen Lü, Linyuan Zhang, Xingyi Lai, Ying-Cheng Zhang, Hai-Feng The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Science Anhui University Hefei230601 China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial Intelligence Anhui University Hefei230601 China Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China Chengdu610054 China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States

Predicting network dynamics based on data, a problem with broad applications, has been studied extensively in the past, but most existing approaches assume that the complete set of historical data from the whole network is available. This requirement presents a great challenge in applications, especially for large, distributed networks in the real world, where data collection is accomplished by many clients in a parallel fashion. Often, each client only has the time series data from a partial set of nodes and the client has access to only partial timestamps of the whole time series data and partial structure of the network. Due to privacy concerns or license related issues, the data collected by different clients cannot be shared. To accurately predict the network dynamics while protecting the privacy of different parties is a critical problem in the modern time. Here, we propose a solution based on federated graph neural networks (FGNNs) that enables the training of a global dynamic model for all parties without data sharing. We validate the working of our FGNN framework through two types of simulations to predict a variety of network dynamics (four discrete and three continuous dynamics). As a significant real-world application, we demonstrate successful prediction of state-wise influenza spreading in the USA. Our FGNN scheme represents a general framework to predict diverse network dynamics through collaborative fusing of the data from different parties without disclosing their privacy. © 2022, CC BY.

关键词： Forecasting

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Antisymmetric planar Hall effect in rutile oxide films induced by the Lorentz force

arXiv

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arXiv 2023年

作者： Cui, Yongwei Li, Zhaoqing Chen, Haoran Wu, Yunzhuo Chen, Yue Pei, Ke Wu, Tong Xie, Nian Che, Renchao Qiu, Xuepeng Liu, Yi Yuan, Zhe Wu, Yizheng Department of Physics State Key Laboratory of Surface Physics Fudan University Shanghai200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Interdisciplinary Center for Theoretical Physics and Information Sciences Fudan University Shanghai200433 China Center for Advanced Quantum Studies Department of Physics Beijing Normal University Beijing100875 China Laboratory of Advanced Materials Shanghai Key Lab of Molecular Catalysis and Innovative Materials Academy for Engineering & Technology Fudan University Shanghai200438 China Shanghai Key Laboratory of Special Artificial Microstructure Materials and Technology School of Physics Science and Engineering Tongji University Shanghai200092 China Zhejiang Laboratory Hangzhou311100 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Shanghai Key Laboratory of Metasurfaces for Light Manipulation Fudan University Shanghai200433 China

The conventional Hall effect is linearly proportional to the field component or magnetization component perpendicular to a film [1]. Despite the increasing theoretical proposals on the Hall effect to the in-plane field or magnetization in various special systems induced by the Berry curvature [2-8], such an unconventional Hall effect has only been experimentally reported in Weyl semimetals and in a heterodimensional superlattice [9-12]. Here, we report an unambiguous experimental observation of the antisymmetric planar Hall effect (APHE) with respect to the in-plane magnetic field in centrosymmetric rutile RuO2 and IrO2 single-crystal films. The measured Hall resistivity is found to be linearly proportional to the component of the applied in-plane magnetic field along a particular crystal axis and to be independent of the current direction or temperature. Both the experimental observations and theoretical calculations confirm that the APHE in rutile oxide films is induced by the Lorentz force. Our findings can be generalized to ferromagnetic materials for the discovery of anomalous Hall effects and quantum anomalous Hall effects induced by in-plane magnetization. In addition to significantly expanding knowledge of the Hall effect, this work opens the door to explore new members in the Hall effect family. Copyright © 2023, The Authors. All rights reserved.

关键词： Crystal symmetry

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Non-invasive assessment of intracranial wall shear stress using high-resolution magnetic resonance imaging in combination with computational fluid dynamics technique

引用

Fundamental Research 2022年第2期2卷 329-334页

作者： Yuwen Chen Jia Liu Mingli Li Yannan Yu Zhengzheng Yan Wenshin Shiu Bokai Wu Zaiheng Cheng Yao Meng Yang Liu Weizhuang Yuan Zongmuyu Zhang Weihai Xu Department of Neurology State Key Laboratory of Complex Severe and Rare DiseasesPeking Union Medical Cllege HospitalChinese Academy of Medical Sciences and Peking Union Medical College1 ShuaifuyuanBeijing 100005China Department of Cardiology Second Afliated Hospital of Zhejiang University School of MedicineHangzhouZhejiang 310009China Shenzhen Instiutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Shenzhen Key Laboratory for Exascale Engineering and Scientific Computing Shenzhen 518055China Department of Radiology Peking Union Medical College HospitalChinese Acadermy of Medical Sciences1 ShuaifiryuanBeijing 100005China Department of Radiology Stanford UniversityCaliformia 94305United States Department of Neurology Saarland UniversityKirrberger StraSe 66421Germany

In vivo studies on association between wall shear stress(WSS)and intracranial plaque are *** on the three-dimensional T1-weighted high-resolution magnetic resonance imaging(3DT1 HR-MRI)data of patients with low-grade stenotic(<50%)atherosclerotic middle cerebral artery(MCA)and subjects with normal MCA,we built a three-dimensional reconstructed WSS model by computational fluid dynamics(CFD)***-dimensional registration of the CFD model to the HR-MRI was performed with projections based on the resolution and thickness of the *** relationships between the Wss at each side of the vessel wall and plaque location were analyzed.A total of 94 MCA plaques from 43 patients and 50 normal MCAs were *** the normal MCAs,WSS was lower at the ventral-inferior wall than at the dorsal-superior wall(proximal segment,p<0.001;middle segment,p<0.001)and lower at the inner wall than at the outer wall of the MCA curve(p<0.001).In atherosclerotic MCAs,similar low Wss regions were observed where plaques *** WSS ratio of the ventral-inferior wall to the dorsal-superior wall in atherosclerotic MCAs was lower than that in normal MCAs(p=0.002).The WSS_(inmer-outer)ratio in atherosclerotic MCAs was lower than that in normal MCAs(p=0.002).Low WSS was associated with MCA atherosclerosis formation and occurred mainly at the ventral inferior wall,which was anatomically opposite the orifices of penetrating arteries,and at the inner wall of the MCA ***,the results were well consistent with the low WSS theory in atherosclerosis *** reconstructed WSS model is a promising novel method for assessing an individualized vascular profile once validated by further studies.

关键词： Intracranial atherosclerosis Wall shear stress Atherosclerotic plaque High-resolution magnetic resonance imaging Computational fluid dynamics

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Unsteady-state and Steady-state Mechanism Analysis of the Oscillatory Flow of Oldroyd-B Fluid in a Tube with a Right Triangular Cross-Section

SSRN

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SSRN 2023年

作者： Liu, Lin Liu, Lang Xie, Chiyu Wang, Lixiu Liu, Yijia Si, Xinhui Feng, Libo School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China State Key Laboratory of Advanced Metallurgy University of Science and Technology Beijing Beijing100083 China School of Civil and Resource Engineering University of Science and Technology Beijing Beijing100083 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQLD4001 Australia

This paper considers the oscillatory flow of the Oldroyd-B fluid in a tube with a right triangular cross-section. The partial differential equation for describing the unidirectional flow of Oldroyd-B fluid is derived. For treating the triangular region, the unstructured mesh finite element method is applied. For verifying the accuracy of the finite element method, the source term is introduced and the exact solution is constructed. We obtain an analytical solution for the steady-state form in the isosceles triangular cross-section tube and analyze the effects of different parameters on the velocity amplitude and phase difference of the Oldroyd-B fluid flow. In addition, the dynamic characteristics for the unsteady-state Oldroyd-B fluid flow are discussed and the influence of the involved parameters, such as the pressure gradient, the relaxation and retardation time parameters on the velocity distribution are also investigated and the flow mechanism is analyzed graphically. At the same condition, we find that only the tube with an isosceles right triangle cross-section can produce the oscillatory flow. © 2023, The Authors. All rights reserved.

关键词： Finite element method

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First-Principles Insights into Complex Interplays Among Nano-Phases in an Al-Cu-Li-Zr Alloy

SSRN

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SSRN 2022年

作者： Liu, Zhengqing Jiang, Yong Wang, Yiren Ma, Peipei Liu, Chunhui State Key Laboratory for Powder Metallurgy School of Materials Science and Engineering Central South University Changsha410083 China Department of Mathematical and Physical Education Yantai Nanshan University Yantai265713 China Light Alloy Research Institute State Key Laboratory of High-Performance Complex Manufacturing Central South University Changsha410083 China Advanced Research Center Central South University Changsha410083 China

Multiple nano-phases and nano-complexes feature the typical microstructures of current commercial Al-Li alloys. We present a combined first-principles and scanning transmission electron microscopy study of various nano-features in an aged Al-Cu-Li-Zr alloy. Many fundamental aspects of their formation and interaction have been elucidated from first-principles energetics. Highly-diffusive excess Li can segregate to the early-precipitated β’(L12 -Al3Zr) nano-phase to develop a tentative δ’(L12 -Al3Li) shell at the early-aging stage. The δ’ shell can promote GP-zone precipitation along the (100) facets but is metastable only, and will eventually dissolve into β’ with time. Consequently, GP-zones can evolve into θ'' and θ’ independently during the prolonged aging. Excess Li weakly segregates to θ’ interfaces to develop an 'in-phase' or 'anti-phase' δ’ shell. The gained insights help clarify various experimental observations, and their implications on Al-Li alloy design are also discussed. © 2022, The Authors. All rights reserved.

关键词： High resolution transmission electron microscopy

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Observation of Dirac Hierarchy in Three-Dimensional Acoustic Topological Insulators

引用

Physical Review Letters 2022年第12期129卷 125502-125502页

作者： Linyun Yang Yin Wang Yan Meng Zhenxiao Zhu Xiang Xi Bei Yan Shuxin Lin Jingming Chen Bin-jie Shi Yong Ge Shou-qi Yuan Hongsheng Chen Hong-xiang Sun Gui-Geng Liu Yihao Yang Zhen Gao Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen 518055 China Research Center of Fluid Machinery Engineering and Technology School of Physics and Electronics Engineering Jiangsu University Zhenjiang 212013 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China ZJU-Hangzhou Global Science and Technology Innovation Center Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems of Zhejiang ZJU-UIUC Institute Zhejiang University Hangzhou 310027 China State Key Laboratory of Acoustics Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore 637371 Singapore

Dirac cones (DCs) play a pivotal role in various unique phenomena ranging from massless electrons in graphene to robust surface states in topological insulators (TIs). Recent studies have theoretically revealed a full Dirac hierarchy comprising an eightfold bulk DC, a fourfold surface DC, and a twofold hinge DC, associated with a hierarchy of topological phases including first-order to third-order three-dimensional (3D) topological insulators, using the same 3D base lattice. Here, we report the first experimental observation of the Dirac hierarchy in 3D acoustic TIs. Using acoustic measurements, we unambiguously reveal that lifting of multifold DCs in each hierarchy can induce two-dimensional topological surface states with a fourfold DC in a first-order 3D TI, one-dimensional topological hinge states with a twofold DC in a second-order 3D TI, and zero-dimensional topological corner states in a third-order 3D TI. Our Letter not only expands the fundamental research scope of Dirac physics, but also opens up a new route for multidimensional robust wave manipulation.

关键词： Topological insulators Acoustic metamaterials

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Analysis of the Absorbing Boundary Condition for the Maxwell Fluid Flow Over a Semi-Infinite Plate with Considering the Magnetic Field

SSRN

引用

SSRN 2023年

作者： Liu, Lin Bao, Chunxu Xie, Chiyu Zhu, Jing Quan, Yufeng Chen, Siyu Feng, Libo Zheng, Liancun School of Mathematics and Physics University of Science and Technology Beijing Beijing100083 China State key laboratory of advanced metallurgy University of Science and Technology Beijing Beijing100083 China School of Civil and Resource Engineering University of Science and Technology Beijing Beijing100083 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQLD4001 Australia

In this paper, we analyze the flow mechanism of the Maxwell fluid over a semi-infinite plate. To handle the semi-infinite boundary, the artificial boundary method is employed and the absorbing boundary condition in the form of convolution is derived. Besides, the stability of the absorbing boundary condition is analyzed. Solutions are obtained numerically using the finite difference method and the accuracy is verified by introducing a source term to construct the exact solution. To demonstrate the validity and reasonableness of the absorbing boundary condition, a comparison with the direct truncation boundary is discussed. Our study examines the effects of the magnetic field, relaxation parameter, oscillation frequency and plate amplitude on the velocity distribution and flow mechanism of the Maxwell fluid. © 2023, The Authors. All rights reserved.

关键词： Numerical methods

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A Novel Malware Detection and Classification Method Based on Capsule Network 5th

A Novel Malware Detection and Classification Method Based on...

引用

5th International Conference on Artificial Intelligence and Security, ICAIS 2019

作者： Wang, Shu-wei Zhou, Gang Lu, Ji-cang Zhang, Feng-juan China State Key Laboratory of Mathematical Engineering and Advanced Computer Zhengzhou450001 China

ISBN: (纸本)9783030242732

By using camouflage technologies such as code confusion, packing and signature, malware could escape the killing of anti-virus software with a high probability. To detect malware efficiently, traditional machine learning methods usually require complex feature extraction work in advance, CNN and other deep learning methods usually need a large number of labeled samples, all of these will affect the detection performance. For these problems, an improved deep learning method (ColCaps) based on malware color image visualization technology and capsule network is proposed in this paper to detect malware. Firstly, the malware is transformed into a color image. Then, the dynamic routing-based capsule network is used to detect and classify the color image. Without advanced feature extraction and with only a small number of labeled samples, ColCaps has better performances in cross-platform detection and classification. The experimental results show that, the detection accuracy of the proposed method on Android and Windows platforms is 99.3% and 96.5% respectively, which is 20% higher than that of the existing method. Meanwhile, the classification task in Drebin dataset has an accuracy of 98.2%, which is a significant improvement over the prior DREBIN. © 2019, Springer Nature Switzerland AG.

关键词： Feature extraction

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