13,446 results match your criteria Chaos Woodbury N.Y.[Journal]


Associations Among Household Chaos, School Belonging and Risk Behaviors in Adolescents.

J Prim Prev 2020 Jul 4. Epub 2020 Jul 4.

Division of Child Development and Community Health, Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA, 92093-0927, USA.

We examined the associations between adolescent risk behaviors and household chaos, and whether associations varied by adolescents' sense of school belonging. We collected data from 801 Chilean adolescents from working-class families (M age 16.2 years). Read More

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http://dx.doi.org/10.1007/s10935-020-00592-2DOI Listing

Chimeras and solitary states in 3D oscillator networks with inertia.

Chaos 2020 Jun;30(6):063113

Scientific Center for Medical and Biotechnical Research, NAS of Ukraine, 54, Volodymyrs'ka St., Kyiv 01030, Ukraine.

We report the diversity of scroll wave chimeras in the three-dimensional (3D) Kuramoto model with inertia for N identical phase oscillators placed in a unit 3D cube with periodic boundary conditions. In the considered model with inertia, we have found patterns that do not exist in a pure system without inertia. In particular, a scroll ring chimera is obtained from random initial conditions. Read More

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http://dx.doi.org/10.1063/5.0005281DOI Listing

Synchronization of thermoacoustic quasiperiodic oscillation by periodic external force.

Chaos 2020 Jun;30(6):063130

Department of Management Science and Technology, Tohoku University, Sendai 980-8579, Japan.

Quasiperiodic oscillations can occur in nonequilibrium systems where two or more frequency components are generated simultaneously. Many studies have explored the synchronization of periodic and chaotic oscillations; however, the synchronization of quasiperiodic oscillations has not received much attention. This study experimentally documents forced synchronization of the quasiperiodic state and the internally locked state of a thermoacoustic oscillator system. Read More

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http://dx.doi.org/10.1063/5.0004381DOI Listing

Forecasting of extreme flood events using different satellite precipitation products and wavelet-based machine learning methods.

Chaos 2020 Jun;30(6):063115

Department of Hydrology, Indian Institute of Technology, Roorkee 247667, India.

An accurate and timely forecast of extreme events can mitigate negative impacts and enhance preparedness. Real-time forecasting of extreme flood events with longer lead times is difficult for regions with sparse rain gauges, and in such situations, satellite precipitation could be a better alternative. Machine learning methods have shown promising results for flood forecasting with minimum variables indicating the underlying nonlinear complex hydrologic system. Read More

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http://dx.doi.org/10.1063/5.0008195DOI Listing

Itinerant complexity in networks of intrinsically bursting neurons.

Chaos 2020 Jun;30(6):061106

Interdisciplinary Program in Neuroscience, Krasnow Institute for Advanced Study, George Mason University, Fairfax, Virginia 22030, USA.

Active neurons can be broadly classified by their intrinsic oscillation patterns into two classes characterized by spiking or bursting. Here, we show that networks of identical bursting neurons with inhibitory pulsatory coupling exhibit itinerant dynamics. Using the relative phases of bursts between neurons, we numerically demonstrate that the network exhibits endogenous transitions between multiple modes of transient synchrony. Read More

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http://dx.doi.org/10.1063/5.0010334DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7311180PMC

Measuring chaos by entropy for a finite family of functions.

Chaos 2020 Jun;30(6):063138

Faculty of Mathematics and Computer Science, Łódź University, Banacha 22, 90-238 Łódź, Poland.

In this paper, we consider chaos of a finite family of continuous functions. As a measure of chaos, we use three types of entropies defined for that family. The first type of entropy is connected with the entropy of semigroups while the second and the third type concern entropy of nonautonomous dynamical systems. Read More

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http://dx.doi.org/10.1063/5.0003905DOI Listing

Nonlinear transport in nonequilibrium systems (with an application to Tokamak-plasmas).

Chaos 2020 Jun;30(6):063110

Departamento de Física-FCFM, Universidad de Chile, Av. Blanco Encalada 2008, Casilla 487-3, CP 837, 0415 Santiago de Chile, Chile.

We show, for the first time, the explicit form of the nonlinear partial differential equations (PDEs) subject to the correct boundary conditions that have to be satisfied by transport coefficients having a vanishing skew-symmetric piece. We also report, for the first time, the nonlinear PDEs (with the appropriate boundary conditions) for transport coefficients when the thermodynamic system is subject to two thermodynamic forces. Since the proposed PDEs have been derived without neglecting any term present in the dynamical equations (i. Read More

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http://dx.doi.org/10.1063/5.0006213DOI Listing

Fear induced explosive transitions in the dynamics of corruption.

Chaos 2020 Jun;30(6):063107

GOTHAM Laboratory, Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018 Zaragoza, Spain.

In this article, we analyze a compartmental model aimed at mimicking the role of imitation and delation of corruption in social systems. In particular, the model relies on a compartmental dynamics in which individuals can transit between three states: honesty, corruption, and ostracism. We model the transitions from honesty to corruption and from corruption to ostracism as pairwise interactions. Read More

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http://dx.doi.org/10.1063/5.0004826DOI Listing

Contrasting chaotic with stochastic dynamics via ordinal transition networks.

Chaos 2020 Jun;30(6):063101

Instituto de Física, Pontificia Universidad Católica de Valparaiso (PUCV), 23-40025 Valparaíso, Chile.

We introduce a representation space to contrast chaotic with stochastic dynamics. Following the complex network representation of a time series through ordinal pattern transitions, we propose to assign each system a position in a two-dimensional plane defined by the permutation entropy of the network (global network quantifier) and the minimum value of the permutation entropy of the nodes (local network quantifier). The numerical analysis of representative chaotic maps and stochastic systems shows that the proposed approach is able to distinguish linear from non-linear dynamical systems by different planar locations. Read More

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http://dx.doi.org/10.1063/1.5142500DOI Listing

Bound states of light bullets in passively mode-locked semiconductor lasers.

Chaos 2020 Jun;30(6):063120

Institute for Theoretical Physics, University of Münster, Wilhelm-Klemm-Str. 9, D-48149 Münster, Germany.

In this paper, we analyze the dynamics and formation mechanisms of bound states (BSs) of light bullets in the output of a laser coupled to a distant saturable absorber. First, we approximate the full three-dimensional set of Haus master equations by a reduced equation governing the dynamics of the transverse profile. This effective theory allows us to perform a detailed multiparameter bifurcation study and to identify the different mechanisms of instability of BSs. Read More

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http://dx.doi.org/10.1063/5.0003227DOI Listing

Analyzing the potential impact of BREXIT on the European research collaboration network.

Chaos 2020 Jun;30(6):063145

Institute for Biocomputation and Physics of Complex Systems (BIFI), University of Zaragoza, 50018 Zaragoza, Spain.

In this work, we study the impact that the withdrawal of institutions from the United Kingdom caused by BREXIT has on the European research collaboration networks. To this aim, we consider BREXIT as a targeted attack to those graphs composed by the European institutions that have collaborated in research projects belonging to the three main H2020 programs (Excellent Science, Industrial Leadership, and Societal Challenges). The consequences of this attack are analyzed at the global, mesoscopic, and local scales and compared with the changes suffered by the same collaboration networks when a similar quantity of nodes is randomly removed from the network. Read More

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http://dx.doi.org/10.1063/1.5139019DOI Listing

Identifying highly influential nodes in multilayer networks based on global propagation.

Chaos 2020 Jun;30(6):061107

Department of Biology and Chemistry, College of Liberal Arts and Sciences, National University of Defense Technology, Changsha, Hunan 410073, China.

Based on percolation theory and the independent cascade model, this paper considers the selection of the optimal propagation source when the propagation probability is greater than the percolation threshold. First, based on the percolation characteristics of real networks, this paper presents an iterative algorithm of linear complexity to solve the probability of the propagation source transmitting information to the network's giant component, that is, the global propagation probability. Compared with the previous multiple local simulation algorithm, this algorithm eliminates random errors and significantly reduces the operation time. Read More

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http://dx.doi.org/10.1063/5.0005602DOI Listing

Relay and complete synchronization in heterogeneous multiplex networks of chaotic maps.

Chaos 2020 Jun;30(6):061104

Department of Physics, Saratov State University, 83 Astrakhanskaya Street, Saratov 410012, Russia.

We study relay and complete synchronization in a heterogeneous triplex network of discrete-time chaotic oscillators. A relay layer and two outer layers, which are not directly coupled but interact via the relay layer, represent rings of nonlocally coupled two-dimensional maps. We consider for the first time the case when the spatiotemporal dynamics of the relay layer is completely different from that of the outer layers. Read More

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http://dx.doi.org/10.1063/5.0008902DOI Listing

Soft-wired long-term memory in a natural recurrent neuronal network.

Chaos 2020 Jun;30(6):061101

Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Dr. Aiguader 88, 08003 Barcelona, Spain.

Recurrent neuronal networks are known to be endowed with fading (short-term) memory, whereas long-term memory is usually considered to be hard-wired in the network connectivity via Hebbian learning, for instance. Here, we use the neuronal network of the roundworm C. elegans to show that recurrent architectures in living organisms can exhibit long-term memory without relying on specific hard-wired modules. Read More

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http://dx.doi.org/10.1063/5.0009709DOI Listing

Universal visibility patterns of unimodal maps.

Chaos 2020 Jun;30(6):063105

Department of Applied Mathematics, Universidad Politécnica de Madrid, 28040 Madrid, Spain.

We apply the horizontal visibility to study the class of unimodal maps that give rise to equivalent bifurcation diagrams. We use the classical logistic map to illustrate the main results of this paper: there are visibility patterns in each cascade of the bifurcation diagram, converging at the onset of chaos. The visibility pattern of a periodic time series is generated from elementary blocks of visibility in a recursive way. Read More

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http://dx.doi.org/10.1063/5.0006652DOI Listing

Does following optimized routes for single cars improve car routing?

Chaos 2020 Jun;30(6):063148

Departamento de Física, Facultad de Ciencias, Universidad de Chile, Casilla 653, Santiago 7800024, Chile.

We study the impact of deserting a pre-established path, determined by a navigation software, on the overall city traffic. To do so, we consider a cellular automaton model for vehicular traffic, where the cars travel between two randomly assigned points in the city following three different navigation strategies based on the minimization of the individual paths or travel times. We found, in general, that, above a critical car density, the transport improves in all strategies if we decrease the time that the vehicles persist in trying to follow a particular strategy when a route is blocked, namely, the mean flux increases, the individual travel times decrease, and the fluctuations of density in the streets decrease; consequently, deserting helps prevent traffic jams. Read More

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http://dx.doi.org/10.1063/1.5145309DOI Listing

Topological localized states in the time delayed Adler model: Bifurcation analysis and interaction law.

Chaos 2020 Jun;30(6):063137

Institute for Theoretical Physics, University of Münster, Wilhelm-Klemm-Str. 9, D-48149 Münster, Germany.

The time-delayed Adler equation is the simplest model for an injected semiconductor laser with coherent injection and optical feedback. It is, however, able to reproduce the existence of topological localized structures (LSs) and their rich interactions. In this paper, we perform the first extended bifurcation analysis of this model and we explore the mechanisms by which LSs emerge. Read More

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http://dx.doi.org/10.1063/5.0002015DOI Listing

Chaotic dynamics of graphene and graphene nanoribbons.

Chaos 2020 Jun;30(6):063150

Department of Mathematics and Applied Mathematics, University of Cape Town, Rondebosch, 7701 Cape Town, South Africa.

We study the chaotic dynamics of graphene structures, considering both a periodic, defect free, graphene sheet and graphene nanoribbons (GNRs) of various widths. By numerically calculating the maximum Lyapunov exponent, we quantify the chaoticity for a spectrum of energies in both systems. We find that for all cases, the chaotic strength increases with the energy density and that the onset of chaos in graphene is slow, becoming evident after more than 10 natural oscillations of the system. Read More

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http://dx.doi.org/10.1063/5.0007761DOI Listing

On the dynamics of the angular momentum of a quantum pendulum.

Chaos 2020 Jun;30(6):063104

Department of Physics, I. Javakhishvili Tbilisi State University, 3, I. Chavchavadze Avenue, 0179 Tbilisi, Georgia.

The Mathieu-Schrödinger equation, which describes the behavior of a quantum pendulum, depending on the value of the parameter l (pendulum filament length), can have the symmetry of the Klein's four-group or its invariant subgroups. The paper shows that the mean values of z-components of the angular momentum of nondegenerate quantum states (the symmetry region of the four-group) tend to zero and their root mean square fluctuations are non-zero. Consequently, in this region of parameter values, the fluctuations overlap the mean values of the angular momentum and they become indistinguishable. Read More

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http://dx.doi.org/10.1063/1.5131093DOI Listing

Synchronization of extreme rainfall during the Australian summer monsoon: Complex network perspectives.

Chaos 2020 Jun;30(6):063117

Helmholtz-Zentrum Potsdam, Deutsches GeoForschungsZentrum GFZ, Telegrafenberg, 14473 Potsdam, Germany.

Monsoon rains are an important fresh water supply for agricultural activity, while extreme rainfalls during a monsoon season frequently cause flash floods. In this study, a nonlinear causation measure of event synchronization is used to set complex networks of extreme rainfall during the Australian summer monsoon (ASM) development between 1st November and 1st March. We adopted Tropical Rainfall Measuring Mission-based satellite rain rate estimates from 1998 to 2015. Read More

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http://dx.doi.org/10.1063/1.5144150DOI Listing

Introduction to Focus Issue: When machine learning meets complex systems: Networks, chaos, and nonlinear dynamics.

Chaos 2020 Jun;30(6):063151

Macedonian Academy of Sciences and Arts, 1000 Skopje, Macedonia.

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http://dx.doi.org/10.1063/5.0016505DOI Listing

Routes to extreme events in dynamical systems: Dynamical and statistical characteristics.

Chaos 2020 Jun;30(6):063114

Department of Mathematics, Jadavpur University, Jadavpur, Kolkata 700032, India.

Intermittent large amplitude events are seen in the temporal evolution of a state variable of many dynamical systems. Such intermittent large events suddenly start appearing in dynamical systems at a critical value of a system parameter and continues for a range of parameter values. Three important processes of instabilities, namely, interior crisis, Pomeau-Manneville intermittency, and the breakdown of quasiperiodic motion, are most common as observed in many systems that lead to such occasional and rare transitions to large amplitude spiking events. Read More

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http://dx.doi.org/10.1063/1.5144143DOI Listing

Avalanche size distribution of an integrate-and-fire neural model on complex networks.

Chaos 2020 Jun;30(6):063118

Department of Physics, Inha University, Incheon 22212, Korea.

We considered the neural avalanche dynamics of a modified integrate-and-fire model on complex networks, as well as the neural dynamics in a fully connected network, random network, small-world network, and scale-free network. We observed the self-organized criticality of the neural model on complex networks. The probability distribution of the avalanche size and lifetime follow the power law at the critical synaptic strength. Read More

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http://dx.doi.org/10.1063/5.0008767DOI Listing

Using curvature to select the time lag for delay reconstruction.

Chaos 2020 Jun;30(6):063143

Department of Applied Mathematics, University of Colorado Boulder, Boulder, Colorado 80309, USA.

We propose a curvature-based approach for choosing a good value for the time-delay parameter τ in delay reconstructions. The idea is based on the effects of the delay on the geometry of the reconstructions. If the delay is too small, the reconstructed dynamics are flattened along the main diagonal of the embedding space; too-large delays, on the other hand, can overfold the dynamics. Read More

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http://dx.doi.org/10.1063/5.0005890DOI Listing

Jackiw-Rebbi states and trivial states in interfaced binary waveguide arrays with cubic-quintic nonlinearity.

Authors:
Truong X Tran

Chaos 2020 Jun;30(6):063134

Department of Physics, Le Quy Don Technical University, 236 Hoang Quoc Viet str., 10000 Hanoi, Vietnam.

We systematically investigate two types of localized states-one is the optical analog of the quantum relativistic Jackiw-Rebbi states and the other is the trivial localized state-in interfaced binary waveguide arrays in the presence of cubic-quintic nonlinearity. By using the shooting method, we can exactly calculate the profiles of these nonlinear localized states. Like in the case with Kerr nonlinearity, we demonstrate that these localized states with cubic-quintic nonlinearity also have an extraordinary property, which completely differs from many well-known nonlinear localized structures in other media. Read More

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http://dx.doi.org/10.1063/5.0004073DOI Listing

Polarity balance for attractor self-reproducing.

Chaos 2020 Jun;30(6):063144

State Key Laboratory of Coal Mine Disaster Dynamics and Control, Chongqing University, Chongqing 400044, China.

There are complex chaotic manifolds in practical nonlinear dynamical systems, especially in nonlinear circuits and chemical engineering. Any system attractor has its own geometric and physical properties, such as granularity, orientation, and spatiotemporal distribution. Polarity balance plays an important role in the solution of a dynamical system including symmetrization, attractor merging, and attractor self-reproducing. Read More

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http://dx.doi.org/10.1063/5.0007668DOI Listing

Reducing network size and improving prediction stability of reservoir computing.

Chaos 2020 Jun;30(6):063136

Institut für Materialphysik im Weltraum, Deutsches Zentrum für Luft- und Raumfahrt, Münchner Str. 20, 82234 Wessling, Germany.

Reservoir computing is a very promising approach for the prediction of complex nonlinear dynamical systems. Besides capturing the exact short-term trajectories of nonlinear systems, it has also proved to reproduce its characteristic long-term properties very accurately. However, predictions do not always work equivalently well. Read More

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http://dx.doi.org/10.1063/5.0006869DOI Listing

Scaling laws and dynamics of hashtags on Twitter.

Chaos 2020 Jun;30(6):063112

School of Mathematics and Statistics, University of Sydney, Sydney, 2006 NSW, Australia.

In this paper, we quantify the statistical properties and dynamics of the frequency of hashtag use on Twitter. Hashtags are special words used in social media to attract attention and to organize content. Looking at the collection of all hashtags used in a period of time, we identify the scaling laws underpinning the hashtag frequency distribution (Zipf's law), the number of unique hashtags as a function of sample size (Heaps' law), and the fluctuations around expected values (Taylor's law). Read More

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http://dx.doi.org/10.1063/5.0004983DOI Listing

Cluster-based dual evolution for multivariate time series: Analyzing COVID-19.

Chaos 2020 Jun;30(6):061108

Yau Mathematical Sciences Center, Tsinghua University, Beijing 100084, China.

This paper proposes a cluster-based method to analyze the evolution of multivariate time series and applies this to the COVID-19 pandemic. On each day, we partition countries into clusters according to both their cases and death counts. The total number of clusters and individual countries' cluster memberships are algorithmically determined. Read More

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http://dx.doi.org/10.1063/5.0013156DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328914PMC

Invertible generalized synchronization: A putative mechanism for implicit learning in neural systems.

Chaos 2020 Jun;30(6):063133

Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

Regardless of the marked differences between biological and artificial neural systems, one fundamental similarity is that they are essentially dynamical systems that can learn to imitate other dynamical systems whose governing equations are unknown. The brain is able to learn the dynamic nature of the physical world via experience; analogously, artificial neural systems such as reservoir computing networks (RCNs) can learn the long-term behavior of complex dynamical systems from data. Recent work has shown that the mechanism of such learning in RCNs is invertible generalized synchronization (IGS). Read More

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http://dx.doi.org/10.1063/5.0004344DOI Listing

Chimera-like states induced by additional dynamic nonlocal wirings.

Chaos 2020 Jun;30(6):063106

Department of Physics, H. H. The Rajah's College (affiliated to Bharathidasan University), Pudukkottai 622 001, Tamil Nadu, India.

We investigate the existence of chimera-like states in a small-world network of chaotically oscillating identical Rössler systems with an addition of randomly switching nonlocal links. By varying the small-world coupling strength, we observe no chimera-like state either in the absence of nonlocal wirings or with static nonlocal wirings. When we give an additional nonlocal wiring to randomly selected nodes and if we allow the random selection of nodes to change with time, we observe the onset of chimera-like states. Read More

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http://dx.doi.org/10.1063/1.5144929DOI Listing

Distributed event-triggered adaptive partial diffusion strategy under dynamic network topology.

Chaos 2020 Jun;30(6):063103

Potsdam Institute for Climate Impact Research, 14473 Potsdam, Germany.

In wireless sensor networks, the dynamic network topology and the limitation of communication resources may lead to degradation of the estimation performance of distributed algorithms. To solve this problem, we propose an event-triggered adaptive partial diffusion least mean-square algorithm (ET-APDLMS). On the one hand, the adaptive partial diffusion strategy adapts to the dynamic topology of the network while ensuring the estimation performance. Read More

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http://dx.doi.org/10.1063/5.0007405DOI Listing

Periodic hematological disorders: Quintessential examples of dynamical diseases.

Authors:
Michael C Mackey

Chaos 2020 Jun;30(6):063123

Department of Physiology, Department of Physics, and Department of Mathematics McGill University, Montreal, Quebec H4X 2C1, Canada.

This paper summarizes the evidence supporting the classification of cyclic neutropenia as a dynamical disease and periodic chronic myelogenous leukemia is also considered. The unsatisfactory state of knowledge concerning the genesis of cyclic thrombocytopenia and periodic autoimmune hemolytic anemia is detailed. Read More

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http://dx.doi.org/10.1063/5.0006517DOI Listing

Recurrence analysis of slow-fast systems.

Chaos 2020 Jun;30(6):063152

Potsdam Institute for Climate Impact Research, P.O. Box 601203, 14412 Potsdam, Germany.

Many complex systems exhibit periodic oscillations comprising slow-fast timescales. In such slow-fast systems, the slow and fast timescales compete to determine the dynamics. In this study, we perform a recurrence analysis on simulated signals from paradigmatic model systems as well as signals obtained from experiments, each of which exhibit slow-fast oscillations. Read More

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http://dx.doi.org/10.1063/1.5144630DOI Listing

Effect of memory, intolerance, and second-order reputation on cooperation.

Chaos 2020 Jun;30(6):063122

Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, 50018 Zaragoza, Spain.

The understanding of cooperative behavior in social systems has been the subject of intense research over the past few decades. In this regard, the theoretical models used to explain cooperation in human societies have been complemented with a growing interest in experimental studies to validate the proposed mechanisms. In this work, we rely on previous experimental findings to build a theoretical model based on two cooperation driving mechanisms: second-order reputation and memory. Read More

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http://dx.doi.org/10.1063/5.0009758DOI Listing

Data-adaptive harmonic analysis of oceanic waves and turbulent flows.

Chaos 2020 Jun;30(6):061105

Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom.

We introduce new features of data-adaptive harmonic decomposition (DAHD) that are showcased to characterize spatiotemporal variability in high-dimensional datasets of complex and mutsicale oceanic flows, offering new perspectives and novel insights. First, we present a didactic example with synthetic data for identification of coherent oceanic waves embedded in high amplitude noise. Then, DAHD is applied to analyze turbulent oceanic flows simulated by the Regional Oceanic Modeling System and an eddy-resolving three-layer quasigeostrophic ocean model, where resulting spectra exhibit a thin line capturing nearly all the energy at a given temporal frequency and showing well-defined scaling behavior across frequencies. Read More

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http://dx.doi.org/10.1063/5.0012077DOI Listing

Extraction of slow and fast dynamics of multiple time scale systems using wavelet techniques.

Chaos 2020 Jun;30(6):063139

Department of Chemistry, Saint Louis University, 3501 Laclede Ave., St. Louis, Missouri 63103, USA.

A methodology is presented based on wavelet techniques to approximate fast and slow dynamics present in time-series whose behavior is characterized by different local scales in time. These approximations are useful to understand the global dynamics of the original full systems, especially in experimental situations where all information is contained in a one-dimensional time-series. Wavelet analysis is a natural approach to handle these approximations because each dynamical behavior manifests its specific subset in frequency domain, for example, with two time scales, the slow and fast dynamics, present in low and high frequencies, respectively. Read More

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http://dx.doi.org/10.1063/5.0004719DOI Listing

Effect of fear on prey-predator dynamics: Exploring the role of prey refuge and additional food.

Chaos 2020 Jun;30(6):063129

Department of Mathematics, National Institute of Technology Agartala, Jirania, West Tripura 799046, India.

The effect of induced fear in the prey due to the presence of a predator can alone develop anti-predator resistance to such an extent that it might reduce the prey reproduction in a significant amount. As fear can perceptibly affect the densities of the terrestrial vertebrates, here we investigate the cost of fear on a Holling type II predator-prey model associated with prey refuge and additional food to the predator. We evidently provide conditions on the existence and stability of equilibria as well as the occurrence of the Hopf bifurcation. Read More

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http://dx.doi.org/10.1063/5.0006968DOI Listing

The tipping times in an Arctic sea ice system under influence of extreme events.

Chaos 2020 Jun;30(6):063125

School of Mathematics, University of Bristol, Fry Building, Woodland Road, Bristol BS8 1UG, United Kingdom.

In light of the rapid recent retreat of Arctic sea ice, the extreme weather events triggering the variability in Arctic ice cover has drawn increasing attention. A non-Gaussian α-stable Lévy process is thought to be an appropriate model to describe such extreme events. The maximal likely trajectory, based on the nonlocal Fokker-Planck equation, is applied to a nonautonomous Arctic sea ice system under α-stable Lévy noise. Read More

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http://dx.doi.org/10.1063/5.0006626DOI Listing

Oscillating synchronization in delayed oscillators with time-varying time delay coupling: Experimental observation.

Chaos 2020 Jun;30(6):063149

Chaos and Complex Systems Research Laboratory, Department of Physics, University of Burdwan, Burdwan 713 104, West Bengal, India.

The time-varying time-delayed (TVTD) systems attract the attention of research communities due to their rich complex dynamics and wide application potentiality. Particularly, coupled TVTD systems show several intriguing behaviors that cannot be observed in systems with a constant delay or no delay. In this context, a new synchronization scenario, namely, oscillating synchronization, was reported by Senthilkumar and Lakshmanan [Chaos 17, 013112 (2007)], which is exclusive to the time-varying time delay systems only. Read More

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http://dx.doi.org/10.1063/5.0003700DOI Listing

Discrete light bullets in passively mode-locked semiconductor lasers.

Chaos 2020 Jun;30(6):063102

Institute for Theoretical Physics, University of Münster, Wilhelm-Klemm-Str. 9, D-48149 Münster, Germany.

In this paper, we analyze the formation and dynamical properties of discrete light bullets in an array of passively mode-locked lasers coupled via evanescent fields in a ring geometry. Using a generic model based upon a system of nearest-neighbor coupled Haus master equations, we show numerically the existence of discrete light bullets for different coupling strengths. In order to reduce the complexity of the analysis, we approximate the full problem by a reduced set of discrete equations governing the dynamics of the transverse profile of the discrete light bullets. Read More

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http://dx.doi.org/10.1063/5.0002989DOI Listing

Stability of bubble-like fluxons in disk-shaped Josephson junctions in the presence of a coaxial dipole current.

Chaos 2020 Jun;30(6):063132

Instituto de Física, Pontificia Universidad Católica de Valparaíso, Casilla 4059, Chile.

We investigate analytically and numerically the stability of bubble-like fluxons in disk-shaped heterogeneous Josephson junctions. Using ring solitons as a model of bubble fluxons in the two-dimensional sine-Gordon equation, we show that the insertion of coaxial dipole currents prevents their collapse. We characterize the onset of instability by introducing a single parameter that couples the radius of the bubble fluxon with the properties of the injected current. Read More

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http://dx.doi.org/10.1063/5.0006226DOI Listing

Identification of chimera using machine learning.

Chaos 2020 Jun;30(6):063128

Complex Systems Lab, Discipline of Physics, Indian Institute of Technology Indore, Khandwa Road, Simrol, 453552 Indore, India.

Chimera state refers to the coexistence of coherent and non-coherent phases in identically coupled dynamical units found in various complex dynamical systems. Identification of chimera, on one hand, is essential due to its applicability in various areas including neuroscience and, on the other hand, is challenging due to its widely varied appearance in different systems and the peculiar nature of its profile. Therefore, a simple yet universal method for its identification remains an open problem. Read More

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http://dx.doi.org/10.1063/1.5143285DOI Listing

Vulnerability in dynamically driven oscillatory networks and power grids.

Chaos 2020 Jun;30(6):063111

Chair for Network Dynamics, Institute for Theoretical Physics and Center for Advancing Electronics Dresden (cfaed), Cluster of Excellence Physics of Life, Technical University of Dresden, 01062 Dresden, Germany.

Vulnerability of networks has so far been quantified mainly for structural properties. In driven systems, however, vulnerability intrinsically relies on the collective response dynamics. As shown recently, dynamic response patterns emerging in driven oscillator networks and AC power grid models are highly heterogeneous and nontrivial, depending jointly on the driving frequency, the interaction topology of the network, and the node or nodes driven. Read More

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http://dx.doi.org/10.1063/1.5122963DOI Listing

Publisher's Note: "Essential chaotic dynamics of chatter in turning processes" [Chaos 30, 053108 (2020)].

Authors:
B Beri G Stepan

Chaos 2020 Jun;30(6):069901

Department of Applied Mechanics, Budapest University of Technology and Economics, P. O. Box 91, H-1521 Budapest, Hungary.

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http://dx.doi.org/10.1063/5.0013076DOI Listing

Topological analysis of SARS CoV-2 main protease.

Authors:
Ernesto Estrada

Chaos 2020 Jun;30(6):061102

Institute of Applied Mathematics (IUMA), Universidad de Zaragoza, Pedro Cerbuna 12, E-50009 Zaragoza, Spain and ARAID Foundation, Government of Aragón, 50018 Zaragoza, Spain.

There is an urgent necessity of effective medication against severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), which is producing the COVID-19 pandemic across the world. Its main protease (M) represents an attractive pharmacological target due to its involvement in essential viral functions. The crystal structure of free M shows a large structural resemblance with the main protease of SARS CoV (nowadays known as SARS CoV-1). Read More

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http://dx.doi.org/10.1063/5.0013029DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7286701PMC

Spontaneous symmetry breaking in purely nonlinear fractional systems.

Chaos 2020 Jun;30(6):063131

State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics of Chinese Academy of Sciences, Xi'an 710119, China.

Spontaneous symmetry breaking, a spontaneous course of breaking the spatial symmetry (parity) of the system, is known to exist in many branches of physics, including condensed-matter physics, high-energy physics, nonlinear optics, and Bose-Einstein condensates. In recent years, the spontaneous symmetry breaking of solitons in nonlinear wave systems is broadly studied; understanding such a phenomenon in nonlinear fractional quantum mechanics with space fractional derivatives (the purely nonlinear fractional systems whose fundamental properties are governed by a nonlinear fractional Schrödinger equation), however, remains pending. Here, we survey symmetry breaking of solitons in fractional systems (with the fractional diffraction order being formulated by the Lévy index α) of a nonlinear double-well structure and find several kinds of soliton families in the forms of symmetric and anti-symmetric soliton states as well as asymmetric states. Read More

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http://dx.doi.org/10.1063/5.0006050DOI Listing

Most probable dynamics of stochastic dynamical systems with exponentially light jump fluctuations.

Chaos 2020 Jun;30(6):063142

Department of Applied Mathematics, Illinois Institute of Technology, Chicago, Illinois 60616, USA.

The emergence of the exit events from a bounded domain containing a stable fixed point induced by non-Gaussian Lévy fluctuations plays a pivotal role in practical physical systems. In the limit of weak noise, we develop a Hamiltonian formalism under the Lévy fluctuations with exponentially light jumps for one- and two-dimensional stochastic dynamical systems. This formalism is based on a recently proved large deviation principle for dynamical systems under non-Gaussian Lévy perturbations. Read More

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http://dx.doi.org/10.1063/5.0006292DOI Listing

Detecting causality from time series in a machine learning framework.

Chaos 2020 Jun;30(6):063116

Meteorological Institute, University of Hamburg, Hamburg 20144, Germany.

Detecting causality from observational data is a challenging problem. Here, we propose a machine learning based causality approach, Reservoir Computing Causality (RCC), in order to systematically identify causal relationships between variables. We demonstrate that RCC is able to identify the causal direction, coupling delay, and causal chain relations from time series. Read More

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http://dx.doi.org/10.1063/5.0007670DOI Listing

Polarizing crowds: Consensus and bipolarization in a persuasive arguments model.

Chaos 2020 Jun;30(6):063141

Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Av. Cantilo s/n, Pabellón 1, Ciudad Universitaria, 1428 Buenos Aires, Argentina.

Understanding the opinion formation dynamics in social systems is of vast relevance in diverse aspects of society. In particular, it is relevant for political deliberation and other group decision-making processes. Although previous research has reported different approaches to model social dynamics, most of them focused on interaction mechanisms where individuals modify their opinions in line with the opinions of others, without invoking a latent mechanism of argumentation. Read More

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http://dx.doi.org/10.1063/5.0004504DOI Listing