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A novel hyperchaotic multistable heterogeneous neural network with hidden attractors and its application in image encryption

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Chinese Journal of Physics 2025年

作者： Zhi Huang Zhen Li Qiao Wang Weijie Tan Xianming Wu College of Big Data and Information Engineering Guizhou University Guiyang 550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang 550025 China Guizhou Key Laboratory of Artificial Intelligence and Brain-inspired Computing College of Mathematics and Big Data Guizhou Education University Guiyang 550018 China State Key Laboratory of Public Big Data Key Laboratory of Advanced Manufacturing Technology of Ministry of Education Guizhou University Guiyang 550025 China School of Mechanical and Electrical Engineering Guizhou Normal University Guiyang 550025 China

By simulating the unique properties of different types of neurons and their interconnecting patterns, heterogeneous neural networks can more accurately reflect the structural and functional characteristics of biological neural systems. Therefore, a novel hyperbolic non-volatile locally active memristor is proposed, enabling the construction of a heterogeneous Hindmarsh-Rose neuron memristive synapse-coupled Hopfield neural network (HR-M-HNN) via synaptic characteristic emulation. Dynamic analysis reveals that the HR-M-HNN exhibits hidden attractor characteristics due to the absence of equilibrium points and can generate complex dynamics behaviors, including hyperchaos, chaos, periodic and quasi-periodic, and multistability. Further research reveals a strong correlation between the chaotic state of HR-M-HNN and the locally active control parameter of the memristor. To verify the accuracy of the dynamic analysis, the corresponding analog circuit is designed. Furthermore, based on the HR-M-HNN hyperchaotic system, a novel image encryption scheme is proposed, which utilizes the position index of the Latin square to perform synchronous permutation and diffusion on the plain image, reducing redundant operations and effectively enhancing the encryption speed. Security analyses demonstrate that the proposed image encryption scheme offers excellent performance and robustness.

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SIP-IFVM: A time-evolving coronal model with an extended magnetic field decomposition strategy

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arXiv 2025年

作者： Wang, Hao P. Yang, Li P. Poedts, S. Lani, A. Zhou, Yu H. Gao, Yu H. Linan, L. Lv, Jia K. Baratashvili, T. Guo, Jing H. Rong, L. Su, Z. Li, Cai X. Zhang, M. Wei, Wen W. Yang, Y. Li, Yu C. Ma, Xin Y. Husidic, E. Jeong, H.-J. Mahdi, Najafi Z. Wang, J. Schmieder, B. Centre for Mathematical Plasma-Astrophysics Department of Mathematics KU Leuven Celestijnenlaan 200B Leuven3001 Belgium State Key Laboratory of Space Weather Chinese Academy of Sciences Beijing100190 China Institute of Physics University of Maria Curie-Sklodowska ul. Radziszewskiego 10 Lublin20-031 Poland Von Karman Institute For Fluid Dynamics Waterloosesteenweg 72 Sint-Genesius-Rode Brussels1640 Belgium School of Earth and Space Sciences Peking University Beijing100871 China Beijing Institute of Applied Meteorology Beijing100029 China School of Astronomy and Space Science Key Laboratory of Modern Astronomy and Astrophysics Nanjing University Nanjing210023 China SIGMA Weather Group State Key Laboratory for Space Weather National Space Science Center Chinese Academy of Sciences Beijing100190 China Shenzhen Key Laboratory of Ultraintense Laser and Advanced Material Technology Center for Intense Laser Application Technology College of Engineering Physics Shenzhen Technology University Shenzhen518118 China Space Sciences Laboratory University of California BerkeleyCA94720 United States School of Mathematical Sciences Nanjing Normal University Nanjing210023 China Ministry of Education Key Laboratory of NSLSCS China College of Earth and Planetary Sciences University of Chinese Academy of Sciences Beijing100049 China School of Systems Science Beijing Normal University Beijing100875 China Meudon Principal F-92195 Cedex France SUPA School of Physics & Astronomy University of Glasgow GlasgowG12 8QQ United Kingdom

Time-evolving magnetohydrodynamic (MHD) coronal modeling, driven by a series of time-dependent photospheric magnetograms, represents a new generation of coronal simulations. This approach offers greater realism compared to traditional coronal models constrained by a static magnetogram. However, its practical application is seriously limited by low computational efficiency and poor numerical stability. Therefore, we propose an extended magnetic field decomposition strategy and implement it in the implicit MHD model to develop a coronal model that is both efficient and numerically stable enough for simulating the long-term evolutions of the global corona. The traditional decomposition strategies split the magnetic field into a time-invariant potential field and a time-dependent component B1. It works well for quasi-steady-state coronal simulations where |B1| is typically small. However, as the inner-boundary magnetic field evolves, |B1| can grow significantly larger and its discretization errors often lead to nonphysical negative thermal pressure, ultimately causing the code to crash. In this paper, we mitigate such undesired situations by introducing a temporally piecewise-constant variable to accommodate part of the non-potential field and remain |B1| consistently small throughout the simulations. We incorporate this novel magnetic field decomposition strategy into our implicit MHD coronal model and apply it to simulate the evolution of coronal structures within 0.1 AU over two solar-maximum Carrington rotations. The results show that this coronal model effectively captures observations and performs more than 80 times faster than real time using only 192 CPU cores, making it well-suited for practical applications in simulating the time-evolving corona. © 2025, CC BY-NC-SA.

关键词： Electric corona

A novel extreme multistability system coupled by HR neuron and unidirectional cyclic HNN and its application in medical image encryption

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Chaos, Solitons & Fractals 2025年 199卷

In brain-like research, investigating the impact of heterogeneous neurons on specific neural network structures is of significant importance. In this paper, a heterogeneous memristive synapse-coupled system (HMSCS) is proposed, which is coupled by Hindmarsh–Rose (HR) and unidirectional cyclic Hopfield neural network (HNN), and is established by presenting a new locally active memristor with multi-stable behavior to simulate the synaptic connection between HR neuron and HNN. The dynamic analysis results show that the locally active region of the memristor can significantly affect the chaos range of HMSCS, and the initial value of the memristor can drive a shift in the phase of the attractor, resulting in extreme multistability. In addition, the numerical analyses are validated by circuit design and simulation. Furthermore, a novel medical image encryption scheme is proposed based on the HMSCS chaotic system, in which an improved Hilbert curve permutation method is given, where the traversal direction and starting point of the Hilbert curve are dynamically selected in each round, thereby effectively enhance permutation performance. Additionally, a region-constrained initial value mapping method is proposed to prevent multistability systems from entering periodic orbits due to improper initial value selection, which is a common problem in existing multistability chaotic systems applied to image encryption. Some common security analyses results show that our proposed encryption scheme has excellent security performance for medical image application scenarios.

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Localization of chiral edge states by the non-Hermitian skin effect

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arXiv 2023年

作者： Liu, Gui-Geng Mandal, Subhaskar Zhou, Peiheng Xi, Xiang Banerjee, Rimi Hu, Yuan-Hang Wei, Minggui Wang, Maoren Wang, Qiang Gao, Zhen Chen, Hongsheng Yang, Yihao Chong, Yidong Zhang, Baile Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link Singapore637371 Singapore National Engineering Research Center of Electromagnetic Radiation Control Materials State Key Laboratory of Electronic Thin Film and Integrated Devices University of Electronic Science and Technology of China Chengdu610054 China Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China School of Physics Collaborative Innovation Center of Advanced Microstructures Nanjing University Jiangsu Nanjing210093 China Interdisciplinary Center for Quantum Information State Key Laboratory of Modern Optical Instrumentation ZJU-Hangzhou Global Science and Technology Innovation Center College of Information Science and Electronic Engineering Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang ZJU-UIUC Institute Zhejiang University Hangzhou310027 China Centre for Disruptive Photonic Technologies The Photonics Institute Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

Quantum Hall systems host chiral edge states extending along the one-dimensional boundary of any two-dimensional sample. In solid state materials, the edge states serve as perfectly robust transport channels that produce a quantised Hall conductance;due to their chirality, and the topological protection by the Chern number of the bulk bandstructure, they cannot be spatially localized by defects or disorder. Here, we show experimentally that the chiral edge states of a lossy quantum Hall system can be localized. In a gyromagnetic photonic crystal exhibiting the quantum Hall topological phase, an appropriately structured loss configuration imparts the edge states’ complex energy spectrum with a feature known as point-gap winding. This intrinsically non-Hermitian topological invariant is distinct from the Chern number invariant of the bulk (which remains intact) and induces mode localization via the "non-Hermitian skin effect". The interplay of the two topological phenomena – the Chern number and point-gap winding – gives rise to a non-Hermitian generalisation of the paradigmatic Chern-type bulk-boundary correspondence principle. Compared to previous realisations of the non-Hermitian skin effect, the skin modes in this system have superior robustness against local defects and disorders. Copyright © 2023, The Authors. All rights reserved.

关键词： Topology

Spinful Topological Phases in Acoustic Crystals with Projective PT Symmetry

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Physical Review Letters 2023年第2期130卷 026101-026101页

作者： Yan Meng Shuxin Lin Bin-jie Shi Bin Wei Linyun Yang Bei Yan Zhenxiao Zhu Xiang Xi Yin Wang Yong Ge Shou-qi Yuan Jingming Chen Gui-Geng Liu Hong-xiang Sun Hongsheng Chen 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 SKLSM Institute of Semiconductors Chinese Academy of Sciences Beijing 100083 China Center for Excellence in Topological Quantum Computation University of 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 State Key Laboratory of Acoustics Institute of Acoustics Chinese Academy of Sciences Beijing 100190 China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou 310027 China International Joint Innovation Center The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua 321099 China Shaoxing Institute of Zhejiang University Zhejiang University Shaoxing 312000 China

For the classification of topological phases of matter, an important consideration is whether a system is spinless or spinful, as these two classes have distinct symmetry algebra that gives rise to fundamentally different topological phases. However, only recently has it been realized theoretically that in the presence of gauge symmetry, the algebraic structure of symmetries can be projectively represented, which possibly enables the switch between spinless and spinful topological phases. Here, we report the experimental demonstration of this idea by realizing spinful topological phases in “spinless” acoustic crystals with projective space-time inversion symmetry. In particular, we realize a one-dimensional topologically gapped phase characterized by a 2Z winding number, which features double-degenerate bands in the entire Brillouin zone and two pairs of degenerate topological boundary modes. Our Letter thus overcomes a fundamental constraint on topological phases by spin classes.

关键词： Acoustics Edge states Topological insulators 1-dimensional systems Finite-element method Gauge symmetries Projective symmetries Tight-binding model

High order asymptotic preserving Hermite WENO fast sweeping method for the steady-state SN transport equation

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arXiv 2021年

作者： Ren, Yupeng Xing, Yulong Wang, Dean Qiu, Jianxian School of Mathematical Sciences Xiamen University XiamenFujian361005 China Department of Mathematics Ohio State University ColumbusOH43210 United States Department of Mechanical and Aerospace Engineering Ohio State University ColumbusOH43210 United States School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific Computing Xiamen University XiamenFujian361005 China

In this paper, we propose to combine the fifth order Hermite weighted essentially non-oscillatory (HWENO) scheme and fast sweeping method (FSM) for the solution of the steady-state SN transport equation in the finite volume framework. It is well-known that the SN transport equation asymptotically converges to a macroscopic diffusion equation in the limit of optically thick systems with small absorption and sources. Numerical methods which can preserve the asymptotic limit are referred to as asymptotic preserving methods. In the one-dimensional case, we provide the analysis to demonstrate the asymptotic preserving property of the high order finite volume HWENO method, by showing that its cell-edge and cell-average fluxes possess the thick diffusion limit. Numerical results in both one- and two- dimensions are presented to validate its asymptotic preserving property. A hybrid strategy to compute the nonlinear weights in the HWENO reconstruction is introduced to save computational cost. Extensive one- and two-dimensional numerical experiments are performed to verify the accuracy, asymptotic preserving property and positivity of the proposed HWENO FSM. Copyright © 2021, The Authors. All rights reserved.

关键词： Diffusion

Design and Implementation of High Performance Cryptographic Service Framework Based on TrustZone

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Design and Implementation of High Performance Cryptographic ...

Information Science, Parallel and Distributed Systems (ISPDS), International Conference on

作者： Lu Yuan Chenlin Huang Lulu Wang Yan Ding Yun Li Hua Cheng Academy of Computer Science National University of Defense Technology Changsha China 31618 Troops Fuzhou China Key Laboratory of Mathematical Engineering and advanced computing Wuxi China

ISBN: (数字)9781728196688

ISBN: (纸本)9781728196695

Due to its favorable isolation and security features, TrustZone technology has been widely used in mobile payment, cloud computing, Internet of Things, etc. However, the cryptographic algorithm provided by the trusted execution environment such as Open-TEE and OP-TEE is inadequate, which brings inconvenience to the development of trusted applications. In addition, the system mainly uses the software algorithms to provide cryptographic services and does not make full use of hardware cryptographic resources, which results in the low efficiency of cryptographic service. To Figure out these two issues, aiming at features of domestic Phytium processors, this paper establishes a unified cryptographic service framework in the TrustZone platform to build a more rich and complete cryptographic algorithm library. Meanwhile, it makes full use of the hardware cryptographic resources of the processor platform to improve the performance of cryptographic service. Test result shows that the proposed framework can bring significant convenience to the development of trusted applications. Meanwhile, compared with the original cryptographic service performance, the cryptographic service provided by the new framework can achieve significant performance improvement.

关键词： Cryptography Routing Performance evaluation Information science

Robust second-order correlation of twin parametric beams generated by amplified spontaneous parametric down-conversion

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Chinese Optics Letters 2020年第12期18卷 63-67页

作者： Kunpeng Jia Xiaohan Wang Xinjie LV Ping Xu Zhenlin Wang ZhiWei Wuang Gang Zhao Yan-Xiao Gong Zhenda Xie Shining Zhu National Laboratory of Solid State Microstructures School of PhysicsSchool of Electronic Science and EngineeringCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China Institute for Quantum Information and State Key Laboratory of High Performance Computing.College of Computing National University of Defense TechnologyChangsha 410073China Mesoscopic Optics and Quantum Electronics Laboratory University of California Los AngelesCciliforniaCA 90095USA

We report an observation of the second-order correlation between twin beams generated by amplified spontaneous parametric down-conversion operating above threshold with kilowatt-level peak power, from a periodically poled Li Ta O3 crystal via a single-pass scheme. Photocurrent correlation was measured because of the bright photon streams, with raw visibility of 37.9% or 97.3% after electronic filtering. As expected in our theory, this correlation is robust and insensitive to parametric gain and detection loss, enabling important applications in optical communications, precision measurement, and nonlocal imaging.

关键词： amplified spontaneous parametric down-con version robust second-order correlation high-gain twin beams

Predicting extreme events from data using deep machine learning: when and where

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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