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information‑entropy enabled identifying topological photonic phase in real space

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Frontiers of Optoelectronics 2024年第2期17卷 1-9页

作者： Rui Ma Qiuchen Yan Yihao Luo Yandong Li Xingyuan Wang Cuicui Lu Xiaoyong Hu Qihuang Gong State Key Laboratory for Mesoscopic Physics&Department of Physics Collaborative Innovation Center of Quantum Matter&Frontiers Science Center for Nano‑OptoelectronicsPeking UniversityBeijing 100871China The MOE Key Laboratory of Weak‑Light Nonlinear Photonics TEDA Applied Physics Institute and School of PhysicsNankai UniversityTianjin 300457China College of Mathematics and Physics Beijing University of Chemical TechnologyBeijing 100029China Laboratory of Advanced Optoelectronic Quantum Architecture and Measurements of Ministry of Education Beijing Key Laboratory of Nanophotonics and Ultrafine Optoelectronic SystemsSchool of PhysicsBeijing Institute of TechnologyBeijing 100081China Peking University Yangtze Delta Institute of Optoelectronics Nantong 226010China Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006China Hefei National Laboratory Hefei 230088China Beijing Academy of Quantum information Sciences Beijing 100193China

The topological photonics plays an important role in the fields of fundamental physics and photonic *** traditional method of designing topological system is based on the momentum space,which is not a direct and convenient way to grasp the topological properties,especially for the perturbative structures or coupled ***,we propose an interdisciplinary approach to study the topological systems in real space through combining the information entropy and topological *** a proof of concept,the Kagome model has been analyzed with information *** reveal that the bandgap closing does not correspond to the topological edge state *** method can be used to identify the topological phase conveniently and directly,even the systems with perturbations or *** a promotional validation,Su-Schrieffer-Heeger model and the valley-Hall photonic crystal have also been studied based on the information entropy *** work provides a method to study topological photonic phase based on information theory,and brings inspiration to analyze the physical properties by taking advantage of interdisciplinarity.

关键词： information entropy Kagome model Topological photonic phase

information entropy for ordinal classification

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Science China(information Sciences) 2010年第6期53卷 1188-1200页

作者： HU QingHua , GUO MaoZu, YU DaRen & LIU JinFu Harbin Institute of Technology, Harbin 150001, China Harbin Institute of Technology Harbin China

Ordinal classification plays an important role in various decision making ***, little attention is paid to this type of learning tasks compared with general classification *** information entropy and the derived measure of mutual information play a fundamental role in a number of learning algorithms including feature evaluation, selection and decision tree *** measures are not applicable to ordinal classification for they cannot characterize the consistency of monotonicity in ordinal *** this paper, we generalize Shannon’s entropy to crisp ordinal classification and fuzzy ordinal classification, and show the information measures of ranking mutual information and fuzzy ranking mutual *** discuss the properties of these measures and show that the proposed ranking mutual information and fuzzy ranking mutual information are the indexes of consistency of monotonicity in ordinal *** addition, the proposed indexes are used to evaluate the monotonicity degree between features and decision in the context of ordinal classification.

关键词： ordinal classification information entropy ranking entropy ranking mutual information

information entropy of Angular Spectrum for Quantitatively Evaluating Eddy Current Distribution Varying in Time Domain

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Journal of Shanghai Jiaotong university(Science) 2023年第5期28卷 587-595页

作者：陈国龙王慷曹政靳伍银 School of Mechanical and Electrical Engineering Lanzhou University of TechnologyLanzhou 730050China

Eddy current (EC) distribution induced by EC sensors determines the interaction between the defectin the testing specimen and the EC, so quantitatively evaluating EC distribution is crucial to the design of ECsensors. In this study, two indices based on the information entropy are proposed to evaluate the EC energyallocated in different directions. The EC vectors induced by a rotational field EC sensor varying in the timedomain are evaluated by the proposed methods. Then, the evaluating results are analyzed by the principle ofEC testing. It can be concluded that the two indices can effectively quantitatively evaluate the EC distributionsvarying in the time domain and are used to optimize the parameters of the rotational EC sensors.

关键词： information entropy eddy current testing non-destructive testing rotational field eddy current probe angular spectrum

Research of Neural Network Structural Optimization Based on information entropy

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Chinese Journal of Electronics 2020年第4期29卷 632-638页

作者： WANG Danyang SHAO Fangming School of Science East China University of Science and Technology

In the application of deep learning, the depth and width of the neural network structure have a great influence on the learning performance of the neural *** paper focuses on structural optimization of depth and width, leveraging the information entropy model and decision tree strategy as feature selection and structural adjustment to optimize neural network ***, a decision tree-based heuristic optimization algorithm for neural network structural adjustment is ***, the proposed approach is applied to fully-connected neural networks trained on the Iris dataset, and the proposed approach is verified effective via experimental simulation.

关键词： information entropy Decision tree Fully connected neural network Heuristic algorithm

Finite-sensor fault-diagnosis simulation study of gas turbine engine using information entropy and deep belief networks

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Frontiers of information Technology & Electronic Engineering 2016年第12期17卷 1287-1304页

作者： De-long FENG Ming-qing XIAO Ying-xi LIU Hai-fang SONG Zhao YANG Ze-wen HU Aeronautics and Astronautics Engineering College Air Force Engineering University Xi'an 710038 China Air Force Xi'an Flight Academy Xi'an 710306 China

Precise fault diagnosis is an important part of prognostics and health management. It can avoid accidents, extend the service life of the machine, and also reduce maintenance costs. For gas turbine engine fault diagnosis, we cannot install too many sensors in the engine because the operating environment of the engine is harsh and the sensors will not work in high temperature, at high rotation speed, or under high pressure. Thus, there is not enough sensory data from the working engine to diagnose potential failures using existing approaches. In this paper, we consider the problem of engine fault diagnosis using finite sensory data under complicated circumstances, and propose deep belief networks based on information entropy, IE-DBNs, for engine fault diagnosis. We first introduce several information entropies and propose joint complexity entropy based on single signal entropy. Second, the deep belief networks （DBNs） is analyzed and a logistic regression layer is added to the output of the DBNs. Then, information entropy is used in fault diagnosis and as the input for the DBNs. Comparison between the proposed IE-DBNs method and state-of-the-art machine learning approaches shows that the IE-DBNs method achieves higher accuracy.

关键词： Deep belief networks (DBNs) Fault diagnosis information entropy Engine

HTDet:A Clustering Method Using information entropy for Hardware Trojan Detection

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Tsinghua Science and Technology 2021年第1期26卷 48-61页

作者： Renjie Lu Haihua Shen Zhihua Feng Huawei Li Wei Zhao Xiaowei Li the University of Chinese Academy of Sciences Beijing 101408China Beijing Institute of Computer Technology and Application Beijing 100854China the State Key Laboratory of Computer Architecture Institute of Computing TechnologyChinese Academy of SciencesBeijing 100190China

Hardware Trojans(HTs)have drawn increasing attention in both academia and industry because of their significant potential *** this paper,we propose HTDet,a novel HT detection method using information entropybased *** maintain high concealment,HTs are usually inserted in the regions with low controllability and low observability,which will result in that Trojan logics have extremely low transitions during the *** implies that the regions with the low transitions will provide much more abundant and more important information for HT *** HTDet applies information theory technology and a density-based clustering algorithm called Density-Based Spatial Clustering of Applications with Noise(DBSCAN)to detect all suspicious Trojan logics in the circuit under *** DBSCAN is an unsupervised learning algorithm,that can improve the applicability of *** addition,we develop a heuristic test pattern generation method using mutual information to increase the transitions of suspicious Trojan *** on circuit benchmarks demonstrate the effectiveness of HTDet.

关键词： Hardware Trojan(HT)detection information entropy Density-Based Spatial Clustering of Applications with Noise(DBSCAN) unsupervised learning clustering mutual information test patterns generation

Predictable component analysis of a system based on nonlinear error information entropy

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Science China Earth Sciences 2017年第3期60卷 501-507页

作者： LI AiBing ZHANG LiFeng LI XinDong LI Wang WANG Bo No.96631 Troops of PLA Beijing 102208China College of Meteorology and Oceanography PLA University of Science and TechnologyNanjing 211101China

Based on the theory of information entropy concerning nonlinear errors, the growth rules for the nonlinear errors of the Lorenz system and its predictable components are studied. The results show that the impact of the uncertainties, both in the initial error and in the system itself, needs to be considered in a quantitative estimation of the system predictability. The nonlinear error growth is related to the magnitude of the initial error, and to the spatial distribution of the initial error vectors. Even if these initial errors have the same magnitude but different directions, there are also differences in the nonlinear error growth. The predictability of nonlinear error growth is related to the error component, but not related to the ratio of these components. The component with the highest/lowest rate of enntribution does not necessarily have the greatest/least predictability. The different components have different predictabilities, and in different time periods, the different predictable components also have different predictabilities.

关键词： Nonlinear error information entropy Predietable component Lorenz system

Δ—scaling and information entropy in Ultra—Relativistic Nucleus—Nucleus Collisions

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Chinese Physics Letters 2003年第7期20卷 1013-1016页

作者：马国亮马余刚王鲲萨本豪沈文本黄焕中蔡翔舟张虎勇卢朝辉钟晨陈金根魏义彬周星飞 ShanghaiInstituteofnuclearResearch ChineseAcademyofSciencesShanghai201800 ChinaInstituteofAtomicEnergy POBox275(18)Beijing102413 DepartmentofPhysics UniversityofCaliforniaLosAngelesCA90095USA

The Δ-scaling method has been applied to ultra-relativistic p+p, C+C and Pb+Pb collision data simulated using a high energy Monte Carlo package, LUCIAE 3.0. The Δ-scaling is found to be valid for some physical variables, such as charged particle multiplicity, strange particle multiplicity and number of binary nucleon-nucleon collisions from these simulated nucleus-nucleus collisions over an extended energy ranging from Elab = 20 to 200 A GeV. In addition we derive the information entropy from the multiplicity distribution as a function of beam energy for these collisions.

关键词： △-scaling information entropy Ultra-Relativistic Nucleus-Nucleus Collisions

Time evolution of information entropy for a stochastic system with double singularities driven by quasimonochromatic noise

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Chinese Physics B 2012年第12期21卷 99-103页

作者：郭永峰谭建国 School of Science Tianjin Polytechnic University

This paper deals with the time evolution of information entropy for a stochastic system with double singularities driven by quasimonochromatic noise. The dimension of the Fokker Planck equation is reduced by the linear transfor- mation. The exact expression of the time dependence of information entropy is obtained based on the definition of Shannon＇s information entropy. The relationships between the properties of dissipative parameters, system singularity strength parameter, quasimonochromatic noise, and their effects on information entropy are discussed.

关键词： information entropy quasimonochromatic noise Fokker-Planck equation stochastic sys-tem with double singularities