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arXiv 2022年

作者： Jiang, Junjie Huang, Zi-Gang Grebogi, Celso Lai, Ying-Cheng The Key Laboratory of Biomedical Information Engineering of Ministry of Education Institute of Health and Rehabilitation Science School of Life Science and Technology Research Center for Brain-inspired Intelligence Xi’an Jiaotong University The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs Shaanxi Xi’an China School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85287 United States Institute for Complex Systems and Mathematical Biology School of Natural and Computing Sciences King’s College University of Aberdeen AB24 3UE United Kingdom Department of Physics Arizona State University TempeAZ85287 United States

We develop a deep convolutional neural network (DCNN) based framework for model-free prediction of the occurrence of extreme events both in time ("when") and in space ("where") in nonlinear physical systems of spatial dimension two. The measurements or data are a set of two-dimensional snapshots or images. For a desired time horizon of prediction, a proper labeling scheme can be designated to enable successful training of the DCNN and subsequent prediction of extreme events in time. Given that an extreme event has been predicted to occur within the time horizon, a space-based labeling scheme can be applied to predict, within certain resolution, the location at which the event will occur. We use synthetic data from the 2D complex Ginzburg-Landau equation and empirical wind speed data of the North Atlantic ocean to demonstrate and validate our machine-learning based prediction framework. The trade-offs among the prediction horizon, spatial resolution, and accuracy are illustrated, and the detrimental effect of spatially biased occurrence of extreme event on prediction accuracy is discussed. The deep learning framework is viable for predicting extreme events in the real world. © 2022, CC BY.

关键词： Forecasting

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Transverse-momentum-dependent wave functions of the pion from lattice QCD

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Physical Review D 2024年第9期109卷 L091503-L091503页

作者： Min-Huan Chu Jin-Chen He Jun Hua Jian Liang Xiangdong Ji Andreas Schäfer Hai-Tao Shu Yushan Su Ji-Hao Wang Wei Wang Yi-Bo Yang Jun Zeng Jian-Hui Zhang Qi-An Zhang INPAC Shanghai Key Laboratory for Particle Physics and Cosmology Key Laboratory for Particle Astrophysics and Cosmology (MOE) School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Yang Yuanqing Scientific Computering Center Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Department of Physics University of Maryland College Park Maryland 20742 USA Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Guangzhou 510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Guangdong Provincial Key Laboratory of Nuclear Science Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 China Institut für Theoretische Physik Universität Regensburg D-93040 Regensburg Germany CAS Key Laboratory of Theoretical Physics Institute of Theoretical Physics Chinese Academy of Sciences Beijing 100190 China School of Fundamental Physics and Mathematical Sciences Hangzhou Institute for Advanced Study UCAS Hangzhou 310024 China Southern Center for Nuclear-Science Theory (SCNT) Institute of Modern Physics Chinese Academy of Sciences Huizhou 516000 Guangdong Province China International Centre for Theoretical Physics Asia-Pacific Beijing/Hangzhou China School of Physical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Science and Engineering The Chinese University of Hong Kong Shenzhen 518172 China Center of Advanced Quantum Studies Department of Physics Beijing Normal University Beijing 100875 China School of Physics Beihang University Beijing 102206 China

We present a lattice QCD calculation of the transverse-momentum-dependent wave function (TMDWF) of the pion using large-momentum effective theory. Numerical simulations are based on one ensemble with 2+1+1 flavors of highly improved staggered quarks with lattice spacing a=0.121 fm from the MILC collaboration, and one with 2+1 flavor clover fermions and tree-level Symanzik gauge action generated by the CLS collaboration with a=0.098 fm. As a key ingredient, the soft function is first obtained by incorporating the one-loop perturbative contributions and a proper normalization. Based on this and the equal-time quasi-TMDWF simulated on the lattice, we extract the TMDWF. The results for both lattice ensembles are compatible and a comparison with a phenomenological parametrization is made. Our studies provide a first attempt of ab initio calculation of TMDWFs which will eventually lead to crucial theory inputs for making predictions for exclusive processes under QCD factorization.

关键词： Lattice QCD Transverse momentum dependent distribution Pions

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Influence of Small-Size Contaminations on Thin Film Structural Properties

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Chinese Physics Letters 2019年第3期36卷 82-85页

作者： F.V.Grigoriev V.B.Sulimov Jinlong Zhang Xinbin Cheng Zhanshan Wang A.V.Tikhonravov Research Computing Center M.V.Lomonosov Moscow State University MOE Key Laboratory of Advanced Micro-Structured Materials Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji University IFSA Collaborative Innovation Center Shanghai Jiao Tong University

An approach for studying the influence of nano-particles on the structural properties of deposited thin films is proposed. It is based on the molecular dynamic modeling of the deposition process in the presence of contaminating nano-particles. The nano-particle is assumed to be immobile and its interaction with film atoms is described by a spherically symmetric potential. The approach is applied to the investigation of properties of silicon dioxide films. Visualization tools are used to investigate the porosity associated with nano-particles. The structure of the film near the nano-particle is studied using the radial distribution function. It is found that fluctuations of film density near the nano-particles are essentially different in the cases of low-energy and high-energy deposition processes.

关键词： Influence Small-Size Properties

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Current switching of the antiferromagnetic Néel vector in Pd/CoO/MgO(001)

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Physical Review B 2022年第21期106卷 214405-214405页

作者： M. Yang Q. Li T. Wang B. Hong C. Klewe Z. Li X. Huang P. Shafer F. Zhang C. Hwang W. S. Yan R. Ramesh W. S. Zhao Y. Z. Wu Xixiang Zhang Z. Q. Qiu Institute of Physical Science and Information Technology Anhui University Hefei Anhui 230601 China National Synchrotron Radiation Laboratory University of Science and Technology of China Hefei Anhui 230029 China Department of Physics University of California Berkeley California 94720 USA Fert Beijing Research Institute School of Integrated Circuit Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Materials Science and Engineering University of California Berkeley California 94720 USA Korea Research Institute of Standards and Science Yuseong Daejeon 305-340 Korea Department of Physics State Key Laboratory of Surface Physics Fudan University Shanghai 200433 China Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal 23955-6900 Saudi Arabia

Recently, the electrical switching of antiferromagnetic (AFM) order has been intensively investigated because of its application potential in data storage technology. Herein, we report the current switching of the AFM Néel vector in epitaxial Pd/CoO films as a function of temperature. Using combined measurements of Hall resistance (HR) and x-ray magnetic linear dichroism (XMLD) below and above the AFM Néel temperature, we unambiguously identified both magnetic and nonmagnetic contributions to the current-induced HR change. Through magnetic field-induced HR measurements, we quantitatively determined the percentage of current-induced CoO spin switching. Further, we showed that the thermal effect dominated the CoO magnetic switching more in samples with a thinner Pd layer and that samples with a thicker CoO layer required higher thermal activation for current-induced magnetic switching. These results provide a clear and comprehensive picture of current-induced AFM spin switching across the AFM Néel temperature.

关键词： Hall effect Magnetism Spintronics X-ray magnetic linear dichroism

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A Novel Timing-based Network Covert Channel Detection Method

A Novel Timing-based Network Covert Channel Detection Method

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作者： Shoupu Lu Zhifeng Chen Guangxin Fu Qingbao Li State Key laboratory of Mathematical Engineering and Advanced Computing Henan University of Economics and Law

Network stealth events are endless,and covert timing channel is one of the most difficult means to *** order to further improve the detection rate of covert timing channel,several typical network covert timing channel construction algorithms are *** the basis of the above analysis,a detection method based on IPDs multidimensional features was proposed in this *** of covert timing channels from three dimensions:shape,change rule and data statistics are ***,polarization feature,autocorrelation feature,clustering feature are proposed,and the three features are unified into a *** threshold method is used to determine whether the channel to be detected is a normal *** show that the method can detect the existing covert timing channel with less time cost and compared with the traditional detection method has a certain rate of improvement.

关键词： IPD A Novel Timing-based Network Covert Channel Detection Method

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Stealthy Malware Detection Based on Deep Neural Network

Stealthy Malware Detection Based on Deep Neural Network

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作者： Shoupu Lu Qingbao Li Xinbing Zhu State Key laboratory of Mathematical Engineering and Advanced Computing Henan University of Economics and Law

Network attacks using advanced local hiding technology have not only increased, but also become a serious threat. However, attacks using these technologies can not be detected through traffic detection, and some attacks imitate benign traffic to avoid detection. To solve these problems, a malware process detection method based on process behavior in possibly infected terminals is proposed. In this method, a deep neural network is introduced to classify malware processes. Firstly, the recurrent neural network is trained to extract the characteristics of process behavior. Secondly, training convolutional neural network is used to classify feature images generated by trained RNN features. The experiments results show that this method can effectively extract the features of malicious processes, and the AUC of ROC curve is 0.97 in the best case.

关键词： ROC image Stealthy Malware Detection Based on Deep Neural Network

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Orbital Magneto-Nonlinear Anomalous Hall Effect in Kagome Magnet Fe3Sn2

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Physical Review Letters 2024年第10期132卷 106601-106601页

作者： Lujunyu Wang Jiaojiao Zhu Haiyun Chen Hui Wang Jinjin Liu Yue-Xin Huang Bingyan Jiang Jiaji Zhao Hengjie Shi Guang Tian Haoyu Wang Yugui Yao Dapeng Yu Zhiwei Wang Cong Xiao Shengyuan A. Yang Xiaosong Wu State Key Laboratory for Artificial Microstructure and Mesoscopic Physics Frontiers Science Center for Nano-optoelectronics Peking University Beijing 100871 China Research Laboratory for Quantum Materials Singapore University of Technology and Design Singapore 487372 Singapore Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore 637371 Singapore Centre for Quantum Physics Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) School of Physics Beijing Institute of Technology Beijing 100081 China School of Sciences Great Bay University Dongguan 523000 China Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems Beijing Institute of Technology Beijing 100081 China Material Science Center Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing China Shenzhen Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China Institute of Applied Physics and Materials Engineering University of Macau Taipa Macau China Department of Physics The University of Hong Kong Hong Kong China HKU-UCAS Joint Institute of Theoretical and Computational Physics at Hong Kong China Collaborative Innovation Center of Quantum Matter Beijing 100871 China Peking University Yangtze Delta Institute of Optoelectronics Nantong 226010 Jiangsu China

It has been theoretically predicted that perturbation of the Berry curvature by electromagnetic fields gives rise to intrinsic nonlinear anomalous Hall effects that are independent of scattering. Two types of nonlinear anomalous Hall effects are expected. The electric nonlinear Hall effect has recently begun to receive attention, while very few studies are concerned with the magneto-nonlinear Hall effect. Here, we combine experiment and first-principles calculations to show that the kagome ferromagnet Fe3Sn2 displays such a magneto-nonlinear Hall effect. By systematic field angular and temperature-dependent transport measurements, we unambiguously identify a large anomalous Hall current that is linear in both applied in-plane electric and magnetic fields, utilizing a unique in-plane configuration. We clarify its dominant orbital origin and connect it to the magneto-nonlinear Hall effect. The effect is governed by the intrinsic quantum geometric properties of Bloch electrons. Our results demonstrate the significance of the quantum geometry of electron wave functions from the orbital degree of freedom and open up a new direction in Hall transport effects.

关键词： Anomalous Hall effect Electronic structure Topological materials Kagome lattice Soft magnets Weyl semimetal

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A short text spectrum clustering method based on frequent itemsets 4

A short text spectrum clustering method based on frequent it...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Luo, Nan Zhang, Ping Li, Qingbao Chen, Zhifeng Feng, Peijun Xue, Tianxiao Engineering and Advanced Computing State Key Laboratory of Mathematical Zhengzhou China

ISBN: (纸本)9781538683392

Short text datum, which contains a lot of useful information, could be easily found on a wide variety of self-media platform and social communication tools. on It is significant to use datum mining technology to automatically acquire knowledge from these datum. However, in short text datum, the word count is small, the text length is short and the information contained is little. Due to all these disadvantages, there are problems of feature sparseness and high information dimensionality. The accuracy of general text mining algorithms is usually unacceptable. This paper proposes a spectral clustering short text analysis method based on frequent itemsets. Firstly, the method cuts the short text datum, and compresses the datum using frequent itemsets. Secondly, a spectral algorithm based on Nyström sampling method is applied to perform clustering and topic extraction on the frequent itemsets. The method effectively solves the problems of feature sparseness and wide dimensions of short text datum. Experiments show that the methodhas better accuracy and performance than the existing algorithms when clustering short texts, and has a good clustering effect. © 2018 IEEE.

关键词： Data mining

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Pdf Exploitable malware analysis based on exploit genes 12

Pdf Exploitable malware analysis based on exploit genes

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12th IEEE International Conference on Anti-Counterfeiting, Security, and Identification, ASID 2018

作者： Zhou, Xin Pang, Jianmin Liu, Fudong Wang, Jun Yue, Feng Liu, Xiaonan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781538660638

With the popularization of social networks, as a low-cost, high-efficiency entail attack method, most of the attack vectors were embedded in email attachments, and exploited vulnerability on Adobe and Office software. Among which PDF-based exploit samples are the main ones. In this paper, we combine bioinformatics and genetics and propose the pdf exploitable malware gene to analyze whether the exploits are exploited in the pdf malware based on software genes. We construct the experiments on the dataset collected from Virus Total filtered by the labels of multiple antivirus software. With the evaluation experiments, the results demonstrate the effectiveness of the pdf exploitable malware gene to detection and classification. © 2018 IEEE.

关键词： Genes

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The research on application of software diversity in cyberspace security 4

The research on application of software diversity in cybersp...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Zhang, Jiexin Pang, Jianmin Zhang, Zheng Liu, Zhenwu State Key Laboratory of Mathematical Engineering and Advanced Computing ZhengZhou China

ISBN: (纸本)9781538683392

Nowadays, the cyberspace security situation is unoptimistic. Widespread vulnerabilities and backdoors are the main factors of insecurity in cyberspace. Furthermore, the software monoculture makes the attack have an extensive impact. This article points out that software vulnerabilities can be used to cope with the security threats from vulnerabilities and backdoors. The paper, firstly, puts forward the shortcomings of the software monoculture, analyzes the validity and application of the software diversity, and points out that the software diversity will play a better role when combined with the redundancy and voting techniques. Then the paper introduces the source of software diversity, and analyzes several security systems which utilize software diversity. Finally, the prospects and challenges of using the software diversity to achieve security systems are summarized. © 2018 IEEE.

关键词： Security systems

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