Subjects -> ENGINEERING (Total: 2844 journals)
    - CHEMICAL ENGINEERING (259 journals)
    - CIVIL ENGINEERING (255 journals)
    - ELECTRICAL ENGINEERING (182 journals)
    - ENGINEERING (1420 journals)
    - ENGINEERING MECHANICS AND MATERIALS (454 journals)
    - HYDRAULIC ENGINEERING (60 journals)
    - INDUSTRIAL ENGINEERING (101 journals)
    - MECHANICAL ENGINEERING (113 journals)

ENGINEERING (1420 journals)                  1 2 3 4 5 6 7 8 | Last

Showing 1 - 200 of 1205 Journals sorted alphabetically
3 Biotech     Open Access   (Followers: 9)
3D Research     Hybrid Journal   (Followers: 22)
AAPG Bulletin     Hybrid Journal   (Followers: 11)
Abstract and Applied Analysis     Open Access   (Followers: 4)
Aceh International Journal of Science and Technology     Open Access   (Followers: 9)
ACS Nano     Hybrid Journal   (Followers: 453)
Acta Geotechnica     Hybrid Journal   (Followers: 7)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 10)
Acta Nova     Open Access   (Followers: 1)
Acta Polytechnica : Journal of Advanced Engineering     Open Access   (Followers: 4)
Acta Scientiarum. Technology     Open Access   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access   (Followers: 1)
Active and Passive Electronic Components     Open Access   (Followers: 8)
Adaptive Behavior     Hybrid Journal   (Followers: 9)
Adsorption     Hybrid Journal   (Followers: 5)
Advanced Energy and Sustainability Research     Open Access   (Followers: 8)
Advanced Engineering Forum     Full-text available via subscription   (Followers: 14)
Advanced Engineering Research     Open Access  
Advanced Journal of Graduate Research     Open Access   (Followers: 4)
Advanced Quantum Technologies     Hybrid Journal   (Followers: 1)
Advanced Science     Open Access   (Followers: 13)
Advanced Science Focus     Free   (Followers: 7)
Advanced Science Letters     Full-text available via subscription   (Followers: 13)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 11)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 20)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 5)
Advances in Catalysis     Full-text available via subscription   (Followers: 8)
Advances in Complex Systems     Hybrid Journal   (Followers: 12)
Advances in Engineering Software     Hybrid Journal   (Followers: 31)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 20)
Advances in Fuzzy Systems     Open Access   (Followers: 5)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 22)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 30)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 27)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 10)
Advances in Natural Sciences : Nanoscience and Nanotechnology     Open Access   (Followers: 36)
Advances in Operations Research     Open Access   (Followers: 14)
Advances in OptoElectronics     Open Access   (Followers: 6)
Advances in Physics Theories and Applications     Open Access   (Followers: 21)
Advances in Polymer Science     Hybrid Journal   (Followers: 54)
Advances in Porous Media     Full-text available via subscription   (Followers: 6)
Advances in Remote Sensing     Open Access   (Followers: 58)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Aerobiologia     Hybrid Journal   (Followers: 4)
Aerospace Systems     Hybrid Journal   (Followers: 10)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 8)
AIChE Journal     Hybrid Journal   (Followers: 38)
Ain Shams Engineering Journal     Open Access   (Followers: 7)
Al-Nahrain Journal for Engineering Sciences     Open Access  
Al-Qadisiya Journal for Engineering Sciences     Open Access   (Followers: 2)
AL-Rafdain Engineering Journal     Open Access   (Followers: 3)
Alexandria Engineering Journal     Open Access   (Followers: 3)
AMB Express     Open Access   (Followers: 1)
American Journal of Applied Sciences     Open Access   (Followers: 27)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 12)
American Journal of Engineering Education     Open Access   (Followers: 20)
American Journal of Environmental Engineering     Open Access   (Followers: 16)
American Journal of Industrial and Business Management     Open Access   (Followers: 31)
Annals of Civil and Environmental Engineering     Open Access   (Followers: 3)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Pure and Applied Logic     Open Access   (Followers: 6)
Annals of Regional Science     Hybrid Journal   (Followers: 10)
Annals of Science     Hybrid Journal   (Followers: 10)
Annual Journal of Technical University of Varna     Open Access   (Followers: 1)
Antarctic Science     Hybrid Journal   (Followers: 1)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 2)
Applications in Energy and Combustion Science     Open Access   (Followers: 3)
Applications in Engineering Science     Open Access   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 8)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 22)
Applied Clay Science     Hybrid Journal   (Followers: 6)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Engineering Letters     Open Access   (Followers: 4)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 4)
Applied Nanoscience     Open Access   (Followers: 11)
Applied Network Science     Open Access   (Followers: 3)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 6)
Applied Physics Research     Open Access   (Followers: 7)
Applied Sciences     Open Access   (Followers: 6)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 6)
Arab Journal of Basic and Applied Sciences     Open Access  
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 5)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 6)
Archives of Thermodynamics     Open Access   (Followers: 13)
Arctic     Open Access   (Followers: 7)
Arid Zone Journal of Engineering, Technology and Environment     Open Access   (Followers: 2)
Arkiv för Matematik     Hybrid Journal   (Followers: 1)
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access   (Followers: 1)
Asia-Pacific Journal of Science and Technology     Open Access  
Asian Engineering Review     Open Access  
Asian Journal of Applied Science and Engineering     Open Access   (Followers: 2)
Asian Journal of Applied Sciences     Open Access   (Followers: 2)
Asian Journal of Biotechnology     Open Access   (Followers: 9)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 7)
Assembly Automation     Hybrid Journal   (Followers: 2)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal  
AURUM : Mühendislik Sistemleri ve Mimarlık Dergisi = Aurum Journal of Engineering Systems and Architecture     Open Access   (Followers: 1)
Australasian Journal of Engineering Education     Hybrid Journal   (Followers: 3)
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Hybrid Journal   (Followers: 2)
Autocracy : Jurnal Otomasi, Kendali, dan Aplikasi Industri     Open Access  
Automotive and Engine Technology     Hybrid Journal  
Automotive Experiences     Open Access  
Automotive Innovation     Hybrid Journal   (Followers: 1)
Avances en Ciencias e Ingenierías     Open Access  
Avances: Investigación en Ingeniería     Open Access   (Followers: 6)
Balkan Region Conference on Engineering and Business Education     Open Access   (Followers: 2)
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 6)
Batteries     Open Access   (Followers: 11)
Batteries & Supercaps     Hybrid Journal   (Followers: 7)
Bautechnik     Hybrid Journal   (Followers: 3)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 29)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 3)
Beyond : Undergraduate Research Journal     Open Access  
Bhakti Persada : Jurnal Aplikasi IPTEKS     Open Access  
Bharatiya Vaigyanik evam Audyogik Anusandhan Patrika (BVAAP)     Open Access   (Followers: 1)
Bilge International Journal of Science and Technology Research     Open Access   (Followers: 1)
Biointerphases     Open Access   (Followers: 1)
Biomaterials Science     Full-text available via subscription   (Followers: 14)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 14)
Biomedical Engineering Letters     Hybrid Journal   (Followers: 6)
Biomedical Engineering: Applications, Basis and Communications     Hybrid Journal   (Followers: 6)
Biomedical Microdevices     Hybrid Journal   (Followers: 9)
Biomedical Science and Engineering     Open Access   (Followers: 8)
Biomicrofluidics     Open Access   (Followers: 7)
Biotechnology Progress     Hybrid Journal   (Followers: 44)
Black Sea Journal of Engineering and Science     Open Access  
Botswana Journal of Technology     Full-text available via subscription   (Followers: 1)
Boundary Value Problems     Open Access   (Followers: 1)
Brazilian Journal of Science and Technology     Open Access   (Followers: 2)
Bulletin of Canadian Petroleum Geology     Full-text available via subscription   (Followers: 13)
Bulletin of Engineering Geology and the Environment     Hybrid Journal   (Followers: 15)
Bulletin of the Crimean Astrophysical Observatory     Hybrid Journal  
Cahiers Droit, Sciences & Technologies     Open Access   (Followers: 1)
Calphad     Hybrid Journal   (Followers: 2)
Canadian Geotechnical Journal     Hybrid Journal   (Followers: 30)
Canadian Journal of Remote Sensing     Full-text available via subscription   (Followers: 50)
Carbon Resources Conversion     Open Access   (Followers: 3)
Carpathian Journal of Electronic and Computer Engineering     Open Access  
Case Studies in Engineering Failure Analysis     Open Access   (Followers: 6)
Case Studies in Thermal Engineering     Open Access   (Followers: 8)
Catalysis Communications     Hybrid Journal   (Followers: 7)
Catalysis Letters     Hybrid Journal   (Followers: 3)
Catalysis Reviews: Science and Engineering     Hybrid Journal   (Followers: 9)
Catalysis Science and Technology     Hybrid Journal   (Followers: 13)
Catalysis Surveys from Asia     Hybrid Journal   (Followers: 4)
Catalysis Today     Hybrid Journal   (Followers: 8)
CEAS Space Journal     Hybrid Journal   (Followers: 6)
Cell Reports Physical Science     Open Access  
Cellular and Molecular Neurobiology     Hybrid Journal   (Followers: 2)
Central European Journal of Engineering     Hybrid Journal  
Chaos : An Interdisciplinary Journal of Nonlinear Science     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 3)
Chinese Journal of Engineering     Open Access   (Followers: 2)
Chinese Journal of Population, Resources and Environment     Open Access  
Chinese Science Bulletin     Open Access   (Followers: 1)
Ciencia e Ingenieria Neogranadina     Open Access  
Ciencia en su PC     Open Access   (Followers: 1)
Ciencia y Tecnología     Open Access  
Ciencias Holguin     Open Access   (Followers: 2)
CienciaUAT     Open Access   (Followers: 1)
Cientifica     Open Access  
CIRP Annals - Manufacturing Technology     Hybrid Journal   (Followers: 11)
CIRP Journal of Manufacturing Science and Technology     Hybrid Journal   (Followers: 14)
City, Culture and Society     Hybrid Journal   (Followers: 27)
Clay Minerals     Hybrid Journal   (Followers: 9)
Coal Science and Technology     Full-text available via subscription   (Followers: 4)
Coastal Engineering     Hybrid Journal   (Followers: 14)
Coastal Engineering Journal     Hybrid Journal   (Followers: 9)
Coastal Engineering Proceedings : Proceedings of the International Conference on Coastal Engineering     Open Access   (Followers: 2)
Coastal Management     Hybrid Journal   (Followers: 30)
Coatings     Open Access   (Followers: 4)
Cogent Engineering     Open Access   (Followers: 3)
Cognitive Computation     Hybrid Journal   (Followers: 3)
Color Research & Application     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 17)
Combustion, Explosion, and Shock Waves     Hybrid Journal   (Followers: 20)
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Communications in Numerical Methods in Engineering     Hybrid Journal   (Followers: 2)
Components, Packaging and Manufacturing Technology, IEEE Transactions on     Hybrid Journal   (Followers: 28)
Composite Interfaces     Hybrid Journal   (Followers: 10)
Composite Structures     Hybrid Journal   (Followers: 336)
Composites Part A : Applied Science and Manufacturing     Hybrid Journal   (Followers: 278)
Composites Part B : Engineering     Hybrid Journal   (Followers: 312)
Composites Part C : Open Access     Open Access   (Followers: 3)
Composites Science and Technology     Hybrid Journal   (Followers: 246)
Comptes Rendus : Mécanique     Open Access   (Followers: 2)
Computation     Open Access   (Followers: 1)
Computational Geosciences     Hybrid Journal   (Followers: 20)
Computational Optimization and Applications     Hybrid Journal   (Followers: 11)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 6)
Computer Science and Engineering     Open Access   (Followers: 21)

        1 2 3 4 5 6 7 8 | Last

Similar Journals
Journal Cover
Chaos : An Interdisciplinary Journal of Nonlinear Science
Journal Prestige (SJR): 0.716
Citation Impact (citeScore): 2
Number of Followers: 3  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1054-1500 - ISSN (Online) 1089-7682
Published by AIP Homepage  [27 journals]
  • Modeling the importance of temporary hospital beds on the dynamics of
           emerged infectious disease

    • Free pre-print version: Loading...

      Authors: A. K. Misra, Jyoti Maurya
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      To explore the impact of available and temporarily arranged hospital beds on the prevention and control of an infectious disease, an epidemic model is proposed and investigated. The stability analysis of the associated equilibria is carried out, and a threshold quantity basic reproduction number ([math]) that governs the disease dynamics is derived and observed whether it depends both on available and temporarily arranged hospital beds. We have used the center manifold theory to derive the normal form and have shown that the proposed model undergoes different types of bifurcations including transcritical (backward and forward), Bogdanov–Takens, and Hopf-bifurcation. Bautin bifurcation is obtained at which the first Lyapunov coefficient vanishes. We have taken advantage of Sotomayor’s theorem to establish the saddle-node bifurcation. Numerical simulations are performed to support the theoretical findings.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:12:07Z
      DOI: 10.1063/5.0064732
       
  • Synchronizability of two-layer correlation networks

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      Authors: Xiang Wei, Xiaoqun Wu, Jun-An Lu, Juan Wei, Junchan Zhao, Yisi Wang
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      This study investigates the synchronizability of a typical type of two-layer correlation networks formed by two regular networks interconnected with two interlayer linking patterns, namely, positive correlation (PC) and negative correlation (NC). To analyze the network’s stability, we consider the analytical expressions of the smallest non-zero and largest eigenvalues of the (weighted) Laplacian matrix as well as the linking strength and the network size for two linking patterns. According to the master stability function, the linking patterns, the linking strength, and the network size associated with two typical synchronized regions exhibit a profound influence on the synchronizability of the two-layer networks. The NC linking pattern displays better synchronizability than the PC linking pattern with the same set of parameters. Furthermore, for the two classical synchronized regions, the networks have optimal intralayer and interlayer linking strengths that maximize the synchronizability while minimizing the required cost. Finally, numerical results verify the validity of the theoretical analyses. The findings based on the representative two-layer correlation networks provide the basis for maximizing the synchronizability of general multiplex correlation networks.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:11:27Z
      DOI: 10.1063/5.0056482
       
  • An efficient continuous data assimilation algorithm for the Sabra shell
           model of turbulence

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      Authors: Nan Chen, Yuchen Li, Evelyn Lunasin
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Complex nonlinear turbulent dynamical systems are ubiquitous in many areas of research. Recovering unobserved state variables is an important topic for the data assimilation of turbulent systems. In this article, an efficient continuous-in-time data assimilation scheme is developed, which exploits closed analytic formulas for updating the unobserved state variables. Therefore, it is computationally efficient and accurate. The new data assimilation scheme is combined with a simple reduced order modeling technique that involves a cheap closure approximation and noise inflation. In such a way, many complicated turbulent dynamical systems can satisfy the requirements of the mathematical structures for the proposed efficient data assimilation scheme. The new data assimilation scheme is then applied to the Sabra shell model, which is a conceptual model for nonlinear turbulence. The goal is to recover the unobserved shell velocities across different spatial scales. It is shown that the new data assimilation scheme is skillful in capturing the nonlinear features of turbulence including the intermittency and extreme events in both the chaotic and the turbulent dynamical regimes. It is also shown that the new data assimilation scheme is more accurate and computationally cheaper than the standard ensemble Kalman filter and nudging data assimilation schemes for assimilating the Sabra shell model with partial observations.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:09:47Z
      DOI: 10.1063/5.0057421
       
  • Spatiotemporal characteristics in systems of diffusively coupled excitable
           slow–fast FitzHugh–Rinzel dynamical neurons

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      Authors: Arnab Mondal, Argha Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay, Chris G. Antonopoulos
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      In this paper, we study an excitable, biophysical system that supports wave propagation of nerve impulses. We consider a slow–fast, FitzHugh–Rinzel neuron model where only the membrane voltage interacts diffusively, giving rise to the formation of spatiotemporal patterns. We focus on local, nonlinear excitations and diverse neural responses in an excitable one- and two-dimensional configuration of diffusively coupled FitzHugh–Rinzel neurons. The study of the emerging spatiotemporal patterns is essential in understanding the working mechanism in different brain areas. We derive analytically the coefficients of the amplitude equations in the vicinity of Hopf bifurcations and characterize various patterns, including spirals exhibiting complex geometric substructures. Furthermore, we derive analytically the condition for the development of antispirals in the neighborhood of the bifurcation point. The emergence of broken target waves can be observed to form spiral-like profiles. The spatial dynamics of the excitable system exhibits two- and multi-arm spirals for small diffusive couplings. Our results reveal a multitude of neural excitabilities and possible conditions for the emergence of spiral-wave formation. Finally, we show that the coupled excitable systems with different firing characteristics participate in a collective behavior that may contribute significantly to irregular neural dynamics.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:08:38Z
      DOI: 10.1063/5.0055389
       
  • Koopman spectral analysis of elementary cellular automata

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      Authors: Keisuke Taga, Yuzuru Kato, Yoshinobu Kawahara, Yoshihiro Yamazaki, Hiroya Nakao
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We perform a Koopman spectral analysis of elementary cellular automata (ECA). By lifting the system dynamics using a one-hot representation of the system state, we derive a matrix representation of the Koopman operator as the transpose of the adjacency matrix of the state-transition network. The Koopman eigenvalues are either zero or on the unit circle in the complex plane, and the associated Koopman eigenfunctions can be explicitly constructed. From the Koopman eigenvalues, we can judge the reversibility, determine the number of connected components in the state-transition network, evaluate the period of asymptotic orbits, and derive the conserved quantities for each system. We numerically calculate the Koopman eigenvalues of all rules of ECA on a one-dimensional lattice of 13 cells with periodic boundary conditions. It is shown that the spectral properties of the Koopman operator reflect Wolfram’s classification of ECA.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:07:05Z
      DOI: 10.1063/5.0059202
       
  • A mechanical analog of Bohr’s atom based on de Broglie’s
           double-solution approach

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      Authors: P. Jamet, A. Drezet
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Motivated by recent developments of hydrodynamical quantum mechanical analogs [J. W. M. Bush, Annu. Rev. Fluid Mech. 47, 269–292 (2015)], we provide a relativistic model for a classical particle coupled to a scalar wave field through a holonomic constraint. In the presence of an external Coulomb field, we define a regime where the particle is guided by the wave in a way similar to the old de Broglie phase-wave proposal. Moreover, this dualistic mechanical analog of the quantum theory is reminiscent of the double-solution approach suggested by de Broglie in 1927 and is able to reproduce the Bohr–Sommerfeld semiclassical quantization formula for an electron moving in an atom.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:06:14Z
      DOI: 10.1063/5.0067545
       
  • Edges of inter-layer synchronization in multilayer networks with
           time-switching links

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      Authors: Muhittin Cenk Eser, Everton S. Medeiros, Mustafa Riza, Anna Zakharova
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We investigate the transition to synchronization in a two-layer network of oscillators with time-switching inter-layer links. We focus on the role of the number of inter-layer links and the timescale of topological changes. Initially, we observe a smooth transition to complete synchronization for the static inter-layer topology by increasing the number of inter-layer links. Next, for a dynamic topology with the existent inter-layer links randomly changing among identical oscillators in the layers, we observe a significant improvement in the system synchronizability; i.e., the layers synchronize with lower inter-layer connectivity. More interestingly, we find that, for a critical switching time, the transition from the network state of low inter-layer synchronization to high inter-layer synchronization occurs abruptly as the number of inter-layer links increases. We interpret this phenomenon as shrinking and ultimately the disappearance of the basin of attraction of a desynchronized network state.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:04:47Z
      DOI: 10.1063/5.0065310
       
  • Assessing time series irreversibility through micro-scale trends

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      Authors: Massimiliano Zanin
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Time irreversibility, defined as the lack of invariance of the statistical properties of a system or time series under the operation of time reversal, has received increasing attention during the last few decades, thanks to the information it provides about the mechanisms underlying the observed dynamics. Following the need of analyzing real-world time series, many irreversibility metrics and tests have been proposed, each one associated with different requirements in terms of, e.g., minimum time series length or computational cost. We here build upon previously proposed tests based on the concept of permutation patterns but deviating from them through the inclusion of information about the amplitude of the signal and how this evolves over time. We show, by means of synthetic time series, that the results yielded by this method are complementary to the ones obtained by using permutation patterns alone, thus suggesting that “one irreversibility metric does not fit all.” We further apply the proposed metric to the analysis of two real-world data sets.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:03:47Z
      DOI: 10.1063/5.0067342
       
  • Machine learning evaluates changes in functional connectivity under a
           prolonged cognitive load

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      Authors: Nikita Frolov, Muhammad Salman Kabir, Vladimir Maksimenko, Alexander Hramov
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      One must be aware of the black-box problem by applying machine learning models to analyze high-dimensional neuroimaging data. It is due to a lack of understanding of the internal algorithms or the input features upon which most models make decisions despite outstanding performance in classification, pattern recognition, and prediction. Here, we approach the fundamentally high-dimensional problem of classifying cognitive brain states based on functional connectivity by selecting and interpreting the most relevant input features. Specifically, we consider the alterations in the cortical synchrony under a prolonged cognitive load. Our study highlights the advances of this machine learning method in building a robust classification model and percept-related prestimulus connectivity changes over the conventional trial-averaged statistical analysis.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-21T09:03:07Z
      DOI: 10.1063/5.0070493
       
  • Sustainable targeted interventions to mitigate the COVID-19 pandemic: A
           big data-driven modeling study in Hong Kong

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      Authors: Hanchu Zhou, Qingpeng Zhang, Zhidong Cao, Helai Huang, Daniel Dajun Zeng
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Nonpharmaceutical interventions (NPIs) for contact suppression have been widely used worldwide, which impose harmful burdens on the well-being of populations and the local economy. The evaluation of alternative NPIs is needed to confront the pandemic with less disruption. By harnessing human mobility data, we develop an agent-based model that can evaluate the efficacies of NPIs with individualized mobility simulations. Based on the model, we propose data-driven targeted interventions to mitigate the COVID-19 pandemic in Hong Kong without city-wide NPIs. We develop a data-driven agent-based model for [math] Hong Kong residents to evaluate the efficacies of various NPIs in the first 80 days of the initial outbreak. The entire territory of Hong Kong has been split into 4905 [math] grids. The model can simulate detailed agent interactions based on the demographics data, public facilities and functional buildings, transportation systems, and travel patterns. The general daily human mobility patterns are adopted from Google’s Community Mobility Report. The scenario without any NPIs is set as the baseline. By simulating the epidemic progression and human movement at the individual level, we propose model-driven targeted interventions which focus on the surgical testing and quarantine of only a small portion of regions instead of enforcing NPIs in the whole city. The effectiveness of common NPIs and the proposed targeted interventions are evaluated by 100 extensive simulations. The proposed model can inform targeted interventions, which are able to effectively contain the COVID-19 outbreak with much lower disruption of the city. It represents a promising approach to sustainable NPIs to help us revive the economy of the city and the world.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-20T03:25:12Z
      DOI: 10.1063/5.0066086
       
  • Decisive conditions for strategic vaccination against SARS-CoV-2

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      Authors: Lucas Böttcher, Jan Nagler
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      While vaccines against severe acute respiratory syndrome coronavirus (SARS-CoV-2) are being administered, in many countries it may still take months until their supply can meet demand. The majority of available vaccines elicit strong immune responses when administered as prime-boost regimens. Since the immunological response to the first (“prime”) dose may provide already a substantial reduction in infectiousness and protection against severe disease, it may be more effective—under certain immunological and epidemiological conditions—to vaccinate as many people as possible with only one dose instead of administering a person a second (“booster”) dose. Such a vaccination campaign may help to more effectively slow down the spread of SARS-CoV-2 and reduce hospitalizations and fatalities. The conditions that make prime-first vaccination favorable over prime-boost campaigns, however, are not well understood. By combining epidemiological modeling, random-sampling techniques, and decision tree learning, we find that prime-first vaccination is robustly favored over prime-boost vaccination campaigns even for low single-dose efficacies. For epidemiological parameters that describe the spread of coronavirus disease 2019 (COVID-19), recent data on new variants included, we show that the difference between prime-boost and single-shot waning rates is the only discriminative threshold, falling in the narrow range of 0.01–0.02 [math] below which prime-first vaccination should be considered.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-20T01:30:53Z
      DOI: 10.1063/5.0066992
       
  • Combining machine learning and data assimilation to forecast dynamical
           systems from noisy partial observations

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      Authors: Georg A. Gottwald, Sebastian Reich
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We present a supervised learning method to learn the propagator map of a dynamical system from partial and noisy observations. In our computationally cheap and easy-to-implement framework, a neural network consisting of random feature maps is trained sequentially by incoming observations within a data assimilation procedure. By employing Takens’s embedding theorem, the network is trained on delay coordinates. We show that the combination of random feature maps and data assimilation, called RAFDA, outperforms standard random feature maps for which the dynamics is learned using batch data.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T04:58:24Z
      DOI: 10.1063/5.0066080
       
  • Reconstructing network structures from partial measurements

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      Authors: Melvyn Tyloo, Robin Delabays, Philippe Jacquod
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      The dynamics of systems of interacting agents is determined by the structure of their coupling network. The knowledge of the latter is, therefore, highly desirable, for instance, to develop efficient control schemes, to accurately predict the dynamics, or to better understand inter-agent processes. In many important and interesting situations, the network structure is not known, however, and previous investigations have shown how it may be inferred from complete measurement time series on each and every agent. These methods implicitly presuppose that, even though the network is not known, all its nodes are. Here, we investigate the different problem of inferring network structures within the observed/measured agents. For symmetrically coupled dynamical systems close to a stable equilibrium, we establish analytically and illustrate numerically that velocity signal correlators encode not only direct couplings, but also geodesic distances in the coupling network within the subset of measurable agents. When dynamical data are accessible for all agents, our method is furthermore algorithmically more efficient than the traditional ones because it does not rely on matrix inversion.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:52:45Z
      DOI: 10.1063/5.0058739
       
  • Study of system dynamics through recurrence analysis of regular windows

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      Authors: A. Rysak, M. Gregorczyk
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      In the recurrence quantification analysis of a dynamical system, the key parameters of the analysis significantly influence the qualitative changes in recurrence measures. Therefore, the values of these parameters must be selected carefully using appropriate rules. The embedding parameters provide rules and procedures for the determination of the above. However, rules for selecting the threshold parameter (ɛ) are still the subject of tests and studies. This study proposes a procedure for selecting appropriate values of ɛ and point density of a vector series based on variability and convergence criteria. A criterion for the linear convergence of recurrence results makes it possible to find a narrow range of the ɛ parameter that would be suitable for the analysis in question.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:48:25Z
      DOI: 10.1063/5.0036505
       
  • Noise-driven topological changes in chaotic dynamics

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      Authors: Gisela D. Charó, Mickaël D. Chekroun, Denisse Sciamarella, Michael Ghil
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Noise modifies the behavior of chaotic systems in both quantitative and qualitative ways. To study these modifications, the present work compares the topological structure of the deterministic Lorenz (1963) attractor with its stochastically perturbed version. The deterministic attractor is well known to be “strange” but it is frozen in time. When driven by multiplicative noise, the Lorenz model’s random attractor (LORA) evolves in time. Algebraic topology sheds light on the most striking effects involved in such an evolution. In order to examine the topological structure of the snapshots that approximate LORA, we use branched manifold analysis through homologies—a technique originally introduced to characterize the topological structure of deterministically chaotic flows—which is being extended herein to nonlinear noise-driven systems. The analysis is performed for a fixed realization of the driving noise at different time instants in time. The results suggest that LORA’s evolution includes sharp transitions that appear as topological tipping points.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:46:05Z
      DOI: 10.1063/5.0059461
       
  • Optimal flatness placement of sensors and actuators for controlling
           chaotic systems

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      Authors: Christophe Letellier, Jean-Pierre Barbot
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Controlling chaotic systems is very often investigated by using empirical laws, without taking advantage of the structure of the governing equations. There are two concepts, observability and controllability, which are inherited from control theory, for selecting the best placement of sensors and actuators. These two concepts can be combined (extended) into flatness, which provides the conditions to fulfill for designing a feedback linearization or another classical control law for which the system is always fully observable and fully controllable. We here design feedback linearization control laws using flatness for the three popular chaotic systems, namely, the Rössler, the driven van der Pol, and the Hénon–Heiles systems. As developed during the last two decades for observability, symbolic controllability coefficients and symbolic flatness coefficients are introduced here and their meanings are tested with numerical simulations. We show that the control law works for every initial condition when the symbolic flatness coefficient is equal to 1.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:44:05Z
      DOI: 10.1063/5.0055895
       
  • Path-integral solution of MacArthur’s resource-competition model for
           large ecosystems with random species-resources couplings

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      Authors: A. R. Batista-Tomás, Andrea De Martino, Roberto Mulet
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We solve MacArthur’s resource-competition model with random species-resource couplings in the “thermodynamic” limit of infinitely many species and resources using dynamical path integrals à la De Domincis. We analyze how the steady state picture changes upon modifying several parameters, including the degree of heterogeneity of metabolic strategies (encoding the preferences of species) and of maximal resource levels (carrying capacities), and discuss its stability. Ultimately, the scenario obtained by other approaches is recovered by analyzing an effective one-species-one-resource ecosystem that is fully equivalent to the original multi-species one. The technique used here can be applied for the analysis of other model ecosystems related to the version of MacArthur’s model considered here.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:42:05Z
      DOI: 10.1063/5.0046972
       
  • Chaos–hyperchaos transition in three identical quorum-sensing mean-field
           coupled ring oscillators

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      Authors: N. Stankevich, E. Volkov
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We investigate the dynamics of three identical three-dimensional ring synthetic genetic oscillators (repressilators) located in different cells and indirectly globally coupled by quorum sensing whereby it is meant that a mechanism in which special signal molecules are produced that, after the fast diffusion mixing and partial dilution in the environment, activate the expression of a target gene, which is different from the gene responsible for their production. Even at low coupling strengths, quorum sensing stimulates the formation of a stable limit cycle, known in the literature as a rotating wave (all variables have identical waveforms shifted by one third of the period), which, at higher coupling strengths, converts to complex tori. Further torus evolution is traced up to its destruction to chaos and the appearance of hyperchaos. We hypothesize that hyperchaos is the result of merging the saddle-focus periodic orbit (or limit cycle) corresponding to the rotating wave regime with chaos and present considerations in favor of this conclusion.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:40:45Z
      DOI: 10.1063/5.0056907
       
  • Chimera states for directed networks

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      Authors: Patrycja Jaros, Roman Levchenko, Tomasz Kapitaniak, Yuri Maistrenko
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We demonstrate that chimera behavior can be observed in ensembles of phase oscillators with unidirectional coupling. For a small network consisting of only three identical oscillators (cyclic triple), tiny chimera islands arise in the parameter space. They are surrounded by developed chaotic switching behavior caused by a collision of rotating waves propagating in opposite directions. For larger networks, as we show for a hundred oscillators (cyclic century), the islands merge into a single chimera continent, which incorporates the world of chimeras of different configurations. The phenomenon inherits from networks with intermediate ranges of the unidirectional coupling and it diminishes as the coupling range decreases.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-12T02:39:15Z
      DOI: 10.1063/5.0059765
       
  • Synchronization of nonlinearly coupled networks based on circle criterion

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      Authors: Sergei A. Plotnikov, Alexander L. Fradkov
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      The problem of synchronization in networks of linear systems with nonlinear diffusive coupling and a connected undirected graph is studied. By means of a coordinate transformation, the system is reduced to the form of mean-field dynamics and a synchronization-error system. The network synchronization conditions are established based on the stability conditions of the synchronization-error system obtained using the circle criterion, and the results are used to derive the condition for synchronization in a network of neural-mass-model populations with a connected undirected graph. Simulation examples are presented to illustrate the obtained results.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-05T02:17:01Z
      DOI: 10.1063/5.0055814
       
  • Analysis of chaotic dynamical systems with autoencoders

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      Authors: N. Almazova, G. D. Barmparis, G. P. Tsironis
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We focus on chaotic dynamical systems and analyze their time series with the use of autoencoders, i.e., configurations of neural networks that map identical output to input. This analysis results in the determination of the latent space dimension of each system and thus determines the minimal number of nodes necessary to capture the essential information contained in the chaotic time series. The constructed chaotic autoencoders generate similar maximal Lyapunov exponents as the original chaotic systems and thus encompass their essential dynamical information.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-05T02:04:01Z
      DOI: 10.1063/5.0055673
       
  • Dynamical ergodicity DDA reveals causal structure in time series

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      Authors: Claudia Lainscsek, Sydney S. Cash, Terrence J. Sejnowski, Jürgen Kurths
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Determining synchronization, causality, and dynamical similarity in highly complex nonlinear systems like brains is challenging. Although distinct, these measures are related by the unknown deterministic structure of the underlying dynamical system. For two systems that are not independent on each other, either because they result from a common process or they are already synchronized, causality measures typically fail. Here, we introduce dynamical ergodicity to assess dynamical similarity between time series and then combine this new measure with cross-dynamical delay differential analysis to estimate causal interactions between time series. We first tested this approach on simulated data from coupled Rössler systems where ground truth was known. We then applied it to intracranial electroencephalographic data from patients with epilepsy and found distinct dynamical states that were highly predictive of epileptic seizures.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-05T02:02:01Z
      DOI: 10.1063/5.0063724
       
  • Dynamics of coupled Kuramoto oscillators with distributed delays

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      Authors: A. Ross, S. N. Kyrychko, K. B. Blyuss, Y. N. Kyrychko
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      This paper studies the effects of two different types of distributed-delay coupling in the system of two mutually coupled Kuramoto oscillators: one where the delay distribution is considered inside the coupling function and the other where the distribution enters outside the coupling function. In both cases, the existence and stability of phase-locked solutions is analyzed for uniform and gamma distribution kernels. The results show that while having the distribution inside the coupling function only changes parameter regions where phase-locked solutions exist, when the distribution is taken outside the coupling function, it affects both the existence, as well as stability properties of in- and anti-phase states. For both distribution types, various branches of phase-locked solutions are computed, and regions of their stability are identified for uniform, weak, and strong gamma distributions.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:14:22Z
      DOI: 10.1063/5.0055467
       
  • Stability of twisted states on lattices of Kuramoto oscillators

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      Authors: Monica Goebel, Matthew S. Mizuhara, Sofia Stepanoff
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Real world systems comprised of coupled oscillators have the ability to exhibit spontaneous synchronization and other complex behaviors. The interplay between the underlying network topology and the emergent dynamics remains a rich area of investigation for both theory and experiment. In this work, we study lattices of coupled Kuramoto oscillators with non-local interactions. Our focus is on the stability of twisted states. These are equilibrium solutions with constant phase shifts between oscillators resulting in spatially linear profiles. Linear stability analysis follows from studying the quadratic form associated with the Jacobian matrix. Novel estimates on both stable and unstable regimes of twisted states are obtained in several cases. Moreover, exploiting the “almost circulant” nature of the Jacobian obtains a surprisingly accurate numerical test for stability. While our focus is on 2D square lattices, we show how our results can be extended to higher dimensions.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:10:42Z
      DOI: 10.1063/5.0060095
       
  • Forecasting wind power ramps with prediction coordinates

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      Authors: Yoshito Hirata, José M. Amigó, Shunsuke Horai, Kazuhiko Ogimoto, Kazuyuki Aihara
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      To the best of our knowledge, the method of prediction coordinates is the only forecasting method in nonlinear time series analysis that explicitly uses the stochastic characteristics of a system with dynamical noise. Specifically, it generates multiple predictions to jointly infer the current states and dynamical noises. Recent findings based on hypothesis testing show that weather is nonlinear and stochastic and, therefore, so are renewable energy power outputs. This being the case, in this paper, we apply the method of prediction coordinates to forecast wind power ramps, which are rapid transitions in the wind power output that can deteriorate the quality of the electricity supply. First, the method of prediction coordinates is tested using numerical simulations. Then, we present an example of wind power ramp forecasting with empirical data. The results show that the method of prediction coordinates compares favorably with other methods, validating it as a reliable tool for forecasting transitions in nonlinear stochastic dynamics, particularly in the field of renewable energies.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:10:02Z
      DOI: 10.1063/5.0061705
       
  • Ill-matched timescales in coupled systems can induce oscillation
           suppression

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      Authors: Sudhanshu Shekhar Chaurasia, Animesh Biswas, P. Parmananda, Sudeshna Sinha
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We explore the behavior of two coupled oscillators, considering combinations of similar and dissimilar oscillators, with their intrinsic dynamics ranging from periodic to chaotic. We first investigate the coupling of two different real-world systems, namely, the chemical mercury beating heart oscillator and the electronic Chua oscillator, with the disparity in the timescales of the constituent oscillators. Here, we are considering a physical situation that is not commonly addressed: the coupling of sub-systems whose characteristic timescales are very different. Our findings indicate that the oscillations in coupled systems are quenched to oscillation death (OD) state, at sufficiently high coupling strength, when there is a large timescale mismatch. In contrast, phase synchronization occurs when their timescales are comparable. In order to further strengthen the concept, we demonstrate this timescale-induced oscillation suppression and phase synchrony through numerical simulations, with the disparity in the timescales serving as a tuning or control parameter. Importantly, oscillation suppression (OD) occurs for a significantly smaller timescale mismatch when the coupled oscillators are chaotic. This suggests that the inherent broad spectrum of timescales underlying chaos aids oscillation suppression, as the temporal complexity of chaotic dynamics lends a natural heterogeneity to the timescales. The diversity of the experimental systems and numerical models we have chosen as a test-bed for the proposed concept lends support to the broad generality of our findings. Last, these results indicate the potential prevention of system failure by small changes in the timescales of the constituent dynamics, suggesting a potent control strategy to stabilize coupled systems to steady states.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:09:22Z
      DOI: 10.1063/5.0059170
       
  • Sensitivity of actuation dynamics on normal and lateral Casimir forces:
           Interaction of phase change and topological insulator materials

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      Authors: F. Tajik, M. Sedighi, G. Palasantzas
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We investigated here the influence of the lateral and normal Casimir force on the actuation dynamics between sinusoidal corrugated surfaces undergoing both normal and lateral displacements. The calculations were performed for topological insulators and phase change materials that are of high interest for device applications. The results show that the lateral Casimir force becomes stronger by increasing the material conductivity and the corrugations toward similar sizes producing wider normal separation changes during lateral motion. In a conservative system, bifurcation and Poincaré portrait analysis shows that larger but similar in size corrugations and/or higher material conductivity favor stable motion along the lateral direction. However, in the normal direction, the system shows higher sensitivity on the optical properties for similar in size corrugations leading to reduced stable operation for higher material conductivity. Furthermore, in non-conservative systems, the Melnikov function with the Poincaré portrait analysis was combined to probe the possible occurrence of chaotic motion. During lateral actuation, systems with more conductive materials and/or the same but high corrugations exhibit lower possibility for chaotic motion. By contrast, during normal motion, chaotic behavior leading to stiction of the moving components is more likely to occur for systems with more conductive materials and similar in magnitude corrugations.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:06:12Z
      DOI: 10.1063/5.0065033
       
  • A study of the double pendulum using polynomial optimization

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      Authors: J. P. Parker, D. Goluskin, G. M. Vasil
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      In dynamical systems governed by differential equations, a guarantee that trajectories emanating from a given set of initial conditions do not enter another given set can be obtained by constructing a barrier function that satisfies certain inequalities on the phase space. Often, these inequalities amount to nonnegativity of polynomials and can be enforced using sum-of-squares conditions, in which case barrier functions can be constructed computationally using convex optimization over polynomials. To study how well such computations can characterize sets of initial conditions in a chaotic system, we use the undamped double pendulum as an example and ask which stationary initial positions do not lead to flipping of the pendulum within a chosen time window. Computations give semialgebraic sets that are close inner approximations to the fractal set of all such initial positions.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:04:42Z
      DOI: 10.1063/5.0061316
       
  • Support vector machines for learning reactive islands

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      Authors: Shibabrat Naik, Vladimír Krajňák, Stephen Wiggins
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We develop a machine learning framework that can be applied to data sets derived from the trajectories of Hamilton’s equations. The goal is to learn the phase space structures that play the governing role for phase space transport relevant to particular applications. Our focus is on learning reactive islands in two degrees-of-freedom Hamiltonian systems. Reactive islands are constructed from the stable and unstable manifolds of unstable periodic orbits and play the role of quantifying transition dynamics. We show that the support vector machines are an appropriate machine learning framework for this purpose as it provides an approach for finding the boundaries between qualitatively distinct dynamical behaviors, which is in the spirit of the phase space transport framework. We show how our method allows us to find reactive islands directly in the sense that we do not have to first compute unstable periodic orbits and their stable and unstable manifolds. We apply our approach to the Hénon–Heiles Hamiltonian system, which is a benchmark system in the dynamical systems community. We discuss different sampling and learning approaches and their advantages and disadvantages.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T02:01:52Z
      DOI: 10.1063/5.0062437
       
  • Ubiquity of ring structures in the control space of complex oscillators

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      Authors: Gonzalo Marcelo Ramírez-Ávila, Jürgen Kurths, Jason A. C. Gallas
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      We report the discovery of two types of stability rings in the control parameter space of a vertical-cavity surface-emitting semiconductor laser. Stability rings are closed parameter paths in the laser control space. Inside such rings, laser stability thrives even in the presence of small parameter fluctuations. Stability rings were also found in rather distinct contexts, namely, in the way that cancerous, normal, and effector cells interact under ionizing radiation and in oscillations of an electronic circuit with a junction-gate field-effect transistor (JFET) diode. We argue that stability-enhancing rings are generic structures present in the control parameter space of many complex systems.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T01:58:11Z
      DOI: 10.1063/5.0066877
       
  • Bohmian trajectories of the time-oscillating Schrödinger equations

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      Authors: Dandan Li, Jinqiao Duan, Li Lin, Ao Zhang
      Abstract: Chaos: An Interdisciplinary Journal of Nonlinear Science, Volume 31, Issue 10, October 2021.
      Bohmian mechanics is a non-relativistic quantum theory based on a particle approach. In this paper, we study the Schrödinger equation with a rapidly oscillating potential and the associated Bohmian trajectory. We prove that the corresponding Bohmian trajectory converges locally in a measure, and the limit coincides with the Bohmian trajectory for the effective Schrödinger equation on a finite time interval. This is beneficial for efficient simulation of the Bohmian trajectories in oscillating potential fields.
      Citation: Chaos: An Interdisciplinary Journal of Nonlinear Science
      PubDate: 2021-10-04T01:57:42Z
      DOI: 10.1063/5.0067645
       
 
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