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The Dynamics and Control of the Fractional Forms of Some Rational Chaotic Maps

Journal of Systems science & Complexity 2020年第3期33卷 584-603页

作者： OUANNAS Adel KHENNAOUI Amina-Aicha BENDOUKHA Samir WANG Zhen PHAM Viet-Thanh Laboratory of Mathematics Informatics and Systems(LAMIS)University of Larbi TebessiTebessa 12002Algeria Department of Mathematics and Computer Sciences University of Larbi Ben M'hidiOum El BouaghiAlgeria Department of Electrical Engineering College of EngineeringYanbuTaibah UniversitySaudi Arabia Shaanxi Engineering Research Center of Controllable Neutron Source School of ScienceXijing UniversityXi'an 710123China Faculty of Electrical and Electronic Engineering Phenikaa Institute for Advanced Study(PIAS)Phenikaa UniversityYen NghiaHa Dong districtHanoi 100000Vietnam Phenikaa Research and Technology Institute(PRATI) A&A Green Phoenix Group167 Hoang NganHanoi 100000Vietnam

This paper proposes three fractional discrete chaotic systems based on the Rulkov,Chang,and Zeraoulia–Sprott rational *** dynamics of the proposed maps are investigated by means of phase plots and bifurcations *** stabilization schemes are proposed for each of the three maps and the convergence of the states is established by using the Lyapunov ***,a combination synchronization scheme is proposed whereby a combination of the fractional Rulkov and Chang maps is synchronized to the fractional Zeraoulia-Sprott *** results are used to confirm the findings of the paper.

关键词： Fractional discrete chaos fractional rational maps stabilization synchronization

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Periodically Driven Open Quantum Systems: Spectral Properties and Non-Equilibrium Steady States

arXiv

引用

arXiv 2023年

作者： Chen, Hao Hu, Yu-Min Zhang, Wucheng Kurniawan, Michael Alexander Shao, Yuelin Chen, Xueqi Prem, Abhinav Dai, Xi Department of Physics Princeton University NJ08544 United States Department of Electrical and Computer Engineering Princeton University NJ08544 United States Institute for Advanced Study Tsinghua University Beijing100084 China Department of Physics Hong Kong University of Science and Technology Clear Water Bay Road Kowloon Hong Kong Beijing National Laboratory for Condensed Matter Physics Institute of Physics Chinese Academy of Sciences Beijing100190 China School of Physical Sciences University of Chinese Academy of Sciences Beijing100049 China Department of Physics Stanford University StanfordCA94305 United States School of Natural Sciences Institute for Advanced Study PrincetonNJ08540 United States

In this article, we investigate periodically driven open quantum systems within the framework of Floquet-Lindblad master equations. Specifically, we discuss Lindblad master equations in the presence of a coherent, time-periodic driving and establish their general spectral features. We also clarify the notions of transient and non-decaying solutions from this spectral perspective, and then prove that any physical system described by a Floquet-Lindblad equation must have at least one physical non-equilibrium steady state (NESS), corresponding to an eigenoperator of the Floquet-Lindblad evolution superoperator UF with unit eigenvalue. Since the Floquet-Lindblad formalism encapsulates the entire information regarding the NESS, it in principle enables us to obtain nonlinear effects to all orders at once. The Floquet-Lindblad formalism thus provides a powerful tool for studying driven-dissipative solid-state systems, which we illustrate by deriving the nonlinear optical response of a simple two-band model of an insulating solid and comparing it with prior results established through Keldysh techniques. © 2023, CC BY-NC-ND.

关键词： Eigenvalues and eigenfunctions

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Bose-Einstein condensation of a two-magnon bound state in a spin-one triangular lattice

arXiv

引用

arXiv 2023年

作者： Sheng, Jieming Mei, Jia-Wei Wang, Le Xu, Xiaoyu Jiang, Wenrui Xu, Lei Ge, Han Zhao, Nan Li, Tiantian Candini, Andrea Xi, Bin Zhao, Jize Fu, Ying Yang, Jiong Zhang, Yuanzhu Biasiol, Giorgio Wang, Shanmin Zhu, Jinlong Miao, Ping Tong, Xin Yu, Dapeng Mole, Richard Cui, Yi Ma, Long Zhang, Zhitao Ouyang, Zhongwen Tong, Wei Podlesnyak, Andrey Wang, Ling Ye, Feng Yu, Dehong Yu, Weiqiang Wu, Liusuo Wang, Zhentao Department of Physics Southern University of Science and Technology Shenzhen518055 China School of Physical Sciences Great Bay University Great Bay Institute for Advanced Study Dongguan523000 China Guangdong Provincial Key Laboratory of Advanced Thermoelectric Materials and Device Physics Department of Physics Southern University of Science and Technology Shenzhen518055 China Shenzhen Institute for Quantum Science and Engineering Shenzhen518055 China Shenzhen Key Laboratory of Advanced Quantum Functional Materials and Devices Southern University of Science and Technology Shenzhen518055 China School of Physics Beijing Key Laboratory of Optoelectronic Functional Materials and Micro-nano Devices Renmin University of China Beijing100872 China School of Physics Zhejiang University Hangzhou310058 China Institute of Organic Synthesis and Photoreactivity National Research Council of Italy ISOF-CNR Via Gobetti 101 Bologna40129 Italy College of Physics Science and Technology Yangzhou University Yangzhou225002 China School of Physical Science and Technology Key Laboratory for Magnetism and Magnetic Materials The MoE Lanzhou University Lanzhou730000 China Lanzhou Center for Theoretical Physics Key Laboratory of Theoretical Physics of Gansu Province Lanzhou University Lanzhou730000 China Shenzhen518045 China Department of Chemistry Southern University of Science and Technology Shenzhen518055 China IOM CNR Laboratorio TASC Area Science Park Basovizza Trieste34149 Italy Beijing100049 China Dongguan523803 China Australian Nuclear Science and Technology Organisation Lucas HeightsNSW2234 Australia Anhui Key Laboratory of Low-Energy Quantum Materials and Devices High Magnetic Field Laboratory Chinese Academy of Sciences Hefei230031 China Wuhan National High Magnetic Field Center School of Physics Huazhong University of Science and Technology Wuhan430074 China Neutron Scattering Division Oak Ridge National Laboratory Oak RidgeTN37831 United S

In ordered magnets, the elementary excitations are spin waves (magnons), which obey Bose-Einstein statistics. Similarly to Cooper pairs in superconductors, magnons can be paired into bound states under attractive interactions. The Zeeman coupling to a magnetic field is able to tune the particle density through a quantum critical point (QCP), beyond which a "hidden order" is predicted to exist. Here we report direct observation of the Bose-Einstein condensation (BEC) of the two-magnon bound state in Na2BaNi(PO4)2. Comprehensive thermodynamic measurements confirmed the two-dimensional BEC-QCP at the saturation field. Inelastic neutron scattering experiments were performed to establish the microscopic model. An exact solution revealed stable 2-magnon bound states that were further confirmed by electron spin resonance and nuclear magnetic resonance experiments, demonstrating that the QCP is due to the pair condensation and the phase below saturation field is likely the long-sought-after spin nematic phase. Copyright © 2023, The Authors. All rights reserved.

关键词： Bose-Einstein condensation

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Hyperspectral Image Reconstruction for Spectral Camera Based on Ghost Imaging Via Sparsity Constraints Using V-Dunet

SSRN

引用

SSRN 2022年

作者： Chen, Ziyan Liu, Zhentao Hu, Chenyu Wu, Heng Wu, Jianrong Lin, Jinda Tong, Zhishen Yu, Hong Han, Shensheng Guangdong Provincial Key Laboratory of Cyber-Physical System School of Automation Guangdong University of Technology Guangzhou510006 China School of Computer Guangdong University of Technology Guangzhou510006 China The Key Laboratory for Quantum Optics of CAS Shanghai Institute of Optics and Fine Mechanics Chinese Academy of Sciences Shanghai201800 China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of Sciences Beijing100049 China Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences Hangzhou310024 China

Spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) obtains three-dimensional (3D) hyperspectral information with two-dimensional (2D) compressive measurements in a single shot, which has attracted much attention in recent years. However, its imaging quality and real-time performance of reconstruction still need to be further improved. Recently, deep learning has shown great potential in improving the reconstruction quality and reconstruction speed for computational imaging. When applying deep learning into GISC spectral camera, there are several challenges need to be solved: 1) how to deal with the large amount of 3D hyperspectral data, 2) how to reduce the influence caused by the uncertainty of the random reference measurements, 3) how to improve the reconstructed image quality as far as possible. In this paper, we present an end-to-end V-DUnet for the reconstruction of 3D hyperspectral data in GISC spectral camera. To reduce the influence caused by the uncertainty of the measurement matrix and enhance the reconstructed image quality, both differential ghost imaging results and the detected measurements are sent into the network’s inputs. Compared with compressive sensing algorithm, such as PICHCS and TwIST, it not only significantly improves the imaging quality with high noise immunity, but also speeds up the reconstruction time by more than two orders of magnitude. © 2022, The Authors. All rights reserved.

关键词： Image reconstruction

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A novel quaternion optimization model for imagined speech classification

引用

Journal of the Franklin Institute 2025年第11期362卷

作者： Zheng, Xiao-Ben Ling, Bingo Wing-Kuen Xu, Nuo Chen, Jian-Rong Zheng, Song-Yi School of Computer Science and Engineering Guangdong Ocean University Yangjiang 529500 China Center for Integrated Circuits and Artificial Intelligence Tsientang Institute for Advanced Study Zhejiang 310024 China School of Information Engineering Guangdong University of Technology Guangzhou 510006 China School of Continuing Education Guangdong Jiangmen Chinese Medical College Jiangmen 529000 China Network and Educational Technology Centre Jinan University Guangzhou Guangdong 510632 China

Imagined speech, characterized by its extensive vocabulary and diverse applications, is a highly promising paradigm in BCI. Multi-channel EEGs are utilized for imagined speech classification. While low rank and sparse representation (LRSR) models have proven useful for EEG processing, they overlook the inter-channel correlations, leading to potential information loss. To address this issue, this paper proposes a quaternion valued LRSR (QLRSR) model for processing the EEGs. Quaternion algebra is a hypercomplex number system extending complex numbers with one real component and three orthogonal imaginary units(i,j,k). Since quaternion can excavate the potential connection of multi-dimensional signals, it is adopted in our QLRSR algorithm for processing muti-channel EEGs. The proposed QLRSR model for imagined speech classification involves two key steps. First, it models sampling points in four-channel EEGs as quaternion-valued numbers, exploiting cross-channel correlations during quaternion operations. Second, the model formulates the QLRSR problem as a quaternion-valued optimization problem. To validate the model's effectiveness, two public datasets are used: Track 3 of the BCI Competition 2020 and the Kara One dataset. By finding the solution of the quaternion valued optimization problem, it is found that the average classification accuracies of our proposed QLRSR model are 64.05 % and 75.46 %, which is higher than the existing models including low rank, sparse, LRSR-based model. Also, the required computational time for performing the classification of the imagined speech via our proposed QLRSR model is 5.12-17.33 % lower than of the aforementioned models. Since QLRSR integrates quaternion algebra into the LRSR-based method, which is more suitable for processing muti-channel signal than LRSR-based method. Hence, our proposed QLRSR model is efficient. Our work in the QLRSR is helpful for the researchers who work on finding a mathematical solution of the quaternion o

关键词： cross correlation Electroencephalogram Imagined speech classification Optimization Quaternion valued low rank and sparse representation

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Prediction of Alzheimer's disease using hybrid machine learning technique

引用

AIP Conference Proceedings 2023年 020091页

作者： M. Senthil Kumar H. Azath A. K. Velmurugan K. Padmanaban Murugan Subbiah Computer Science and Engineering Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science And Technology Chennai Tamil Nadu India School of Computing Science and Engineering VIT Bhopal University India Computer Science and Engineering Koneru Lakshmaiah Education Foundation Green Field Vaddeswaram Guntur Dist. Vijayawada Andhra Pradesh-522502 India Vee Eee Technologies Chennai Tamil Nadu India

Alzheimer's infection (AD) is a neurodegenerative illness and the most widely recognized reason for Dementia in more seasoned grown-ups. The piece of cerebrum that gets influenced by this illness is hippocampus degeneration. The Discovery of Alzheimer's sickness at the fundamental stage is vital as it can forestall genuine harm to the patient's mind. It becomes hazardous and here and there lethal in the event of individuals 65 years old or above. To fulfil the expectation, CNN calculations were used. The suggested technique has obtained a 20 percent improvement in characterisation accuracy, which is contrasted with conventional procedures, and suggests that neural organism is a tremendous advantage for neurological disease analysis. Due to our study, the analysis of different neurological diseases using intelligent medical services frameworks may be done by comparable or comparative *** principal objective of this paper is to utilize Hybrid AI calculations that coordinate SVM with CNN and component extraction and determination to anticipate Alzheimer's sickness and fabricate a helpful model. The dataset is taken as MRI pictures. The proposed approach identifies the different phases of Alzheimer's infection, for example, moderate-unbalanced and no sick utilizing CNN calculation.

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Theory of Pressure-Induced Rejuvenation and Strain Hardening in Metallic Glasses

引用

Physical Review Letters 2021年第2期126卷 025502-025502页

作者： Anh D. Phan Alessio Zaccone Vu D. Lam Katsunori Wakabayashi Faculty of Materials Science and Engineering Computer Science Artificial Intelligence Laboratory Phenikaa Institute for Advanced Study Phenikaa University Hanoi 12116 Vietnam Department of Nanotechnology for Sustainable Energy School of Science and Technology Kwansei Gakuin University Sanda Hyogo 669-1337 Japan Department of Physics “A. Pontremoli” University of Milan via Celoria 16 20133 Milano Italy Cavendish Laboratory University of Cambridge JJ Thomson Avenue CB3 0HE Cambridge United Kingdom Department of Chemical Engineering and Biotechnology Statistical Physics Group University of Cambridge Philippa Fawcett Drive CB3 0AS Cambridge United Kingdom Institute of Materials Science Vietnam Academy of Science and Technology Hanoi 100000 Vietnam Graduate University of Science and Technology Vietnam Academy of Science and Technology Hanoi 100000 Vietnam

We theoretically investigate high-pressure effects on the atomic dynamics of metallic glasses. The theory predicts compression-induced rejuvenation and the resulting strain hardening that have been recently observed in metallic glasses. Structural relaxation under pressure is mainly governed by local cage dynamics. The external pressure restricts the dynamical constraints and slows down the atomic mobility. In addition, the compression induces a rejuvenated metastable state (local minimum) at a higher energy in the free-energy landscape. Thus, compressed metallic glasses can rejuvenate and the corresponding relaxation is reversible. This behavior leads to strain hardening in mechanical deformation experiments. Theoretical predictions agree well with experiments.

关键词： Plastic deformation Pressure effects Strain Glassy systems Metallic glasses Metals

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Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

arXiv

引用

arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Institute for Advanced Study Tongji University Shanghai China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

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Editorial for the Special Issue on Laser Micro/Nano-Manufacturing

引用

engineering 2025年

作者： Hong, Minghui Chen, Lianwei Cao, Tun Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen University Xiamen361005 China Department of Electrical and Computer Engineering National University of Singapore Singapore117576 Singapore National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of Sciences Chengdu610209 China State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering Institute of Optics and Electronics Chinese Academy of Sciences Chengdu610209 China School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian116024 China

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Laser Micro/Nano-Manufacturing

引用

engineering 2025年

作者： Minghui Hong Lianwei Chen Tun Cao Pen-Tung Sah Institute of Micro-Nano Science and Technology Xiamen University Xiamen 361005 China Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of Sciences Chengdu 610209 China State Key Laboratory of Optical Technologies on Nano-Fabrication and Micro-Engineering Institute of Optics and Electronics Chinese Academy of Sciences Chengdu 610209 China School of Optoelectronic Engineering and Instrumentation Science Dalian University of Technology Dalian 116024 China

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