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The stickiness effect is a fundamental feature of quasi-integrable Hamiltonian systems. We propose the use of an entropy-based measure of the recurrence plots (RP), namely, the entropy of the distribution of the recurrence times (estimated from the RP), to characterize the dynamics of a typical quasi-integrable Hamiltonian system with coexisting regular and chaotic regions. We show that the recurrence time entropy (RTE) is positively correlated to the largest Lyapunov exponent, with a high correlation coefficient. We obtain a multi-modal distribution of the finite-time RTE and find that each mode corresponds to the motion around islands of different hierarchical levels., 16 pages, 7 figures

Intrinsically coupled nonlinear systems present different oscillating components that exchange energy among themselves. A paradigmatic example is the spring pendulum, which displays spring, pendulum, and coupled oscillations. We analyze the energy exchanges among the oscillations, and obtain that it is enhanced for chaotic orbits. Moreover, the highest rates of energy exchange for the coupling occur along the homoclinic tangle of the primary hyperbolic point embedded in a chaotic sea. The results show a clear relation between internal energy exchanges and the dynamics of a coupled system., Submitted for publication

In this work, we investigate the presence of sub-diffusive behavior in the Chirikov-Taylor Standard Map. We show that the stickiness phenomena, present in the mixed phase space of the map setup, can be characterized as a Continuous Time Random Walk model and connected to the theoretical background for anomalous diffusion. Additionally, we choose a variant of the Ulam method to numerically approximate the Perron-Frobenius operator for the map, allowing us to calculate the anomalous diffusion exponent via an eigenvalue problem, compared to the solution of the Fractional Diffusion Equation. The results here corroborate other findings in the literature of anomalous transport in Hamiltonian maps and can be suitable to describe transport properties of other dynamical systems., Submitted to EPJ-ST

Area-preserving nontwist maps are used to describe a broad range of physical systems. In those systems, the violation of the twist condition leads to nontwist characteristic phenomena, such as reconnection-collision sequences and shearless invariant curves that act as transport barriers in the phase space. Although reported in numerical investigations, the shearless bifurcation, i.e., the emergence scenario of multiple shearless curves, is not well understood. In this work, we derive an area-preserving map as a local approximation of a particle transport model for confined plasmas. Multiple shearless curves are found in this area-preserving map, with the same shearless bifurcation scenario numerically observed in the original model. Due to its symmetry properties and simple functional form, this map is proposed as a model to study shearless bifurcations., 16 pages, 10 figures

Osciladores de fase são sistemas dinâmicos dissipativos com aporte externo de energia, e matematicamente caracterizados pela presença de ciclos-limite, ao longo dos quais a dinâmica pode ser descrita por um ângulo de fase. No presente artigo, consideramos fenômenos de sincronização num sistema de muitos osciladores de fase acoplados. Adotamos uma descrição qualitativa, baseada num modelo paradigmático proposto por Y. Kuramoto em 1975. Discutimos, à luz dessa descrição, algumas aplicações em sistemas físicos (metrônomos e pedestres numa ponte pênsil) e biológicos (neurônios e vagalumes piscando). Phase oscillators are dissipative dynamic systems with external energy input, and mathematically characterized by the presence of limit cycles, along which the dynamics can be described by a phase angle. In the present article, we consider synchronization phenomena in a system of many phase-coupled oscillators. We adopt a qualitative description, based on a paradigmatic model proposed by Y. Kuramoto in 1975. We discuss, in the light of this description, some applications in physical systems (metronomes and pedestrians on a suspension bridge) and biological (neurons and fireflies blinking).

We study the time delay in the synaptic conductance for suppression of spike synchronisation in a random network of Hodgkin Huxley neurons coupled by means of chemical synapses. In the first part, we examine in detail how the time delay acts over the network during the synchronised and desynchronised neuronal activities. We observe a relation between the neuronal dynamics and the syaptic conductance distributions. We find parameter values in which the time delay has high effectiveness in promoting the suppression of spike synchronisation. In the second part, we analyse how the delayed neuronal networks react when pulsed inputs with different profiles (periodic, random, and mixed) are applied on the neurons. We show the main parameters responsible for inducing or not synchronous neuronal oscillations in delayed networks.

In this work, we study the unpredictability of seasonal infectious diseases considering a SEIRS model with seasonal forcing. To investigate the dynamical behaviour, we compute bifurcation diagrams type hysteresis and their respective Lyapunov exponents. Our results from bifurcations and the largest Lyapunov exponent show bistable dynamics for all the parameters of the model. Choosing the inverse of latent period as control parameter, over 70% of the interval comprises the coexistence of periodic and chaotic attractors, bistable dynamics. Despite the competition between these attractors, the chaotic ones are preferred. The bistability occurs in two wide regions. One of these regions is limited by periodic attractors, while periodic and chaotic attractors bound the other. As the boundary of the second bistable region is composed of periodic and chaotic attractors, it is possible to interpret these critical points as tipping points. In other words, depending on the latent period, a periodic attractor (predictability) can evolve to a chaotic attractor (unpredictability). Therefore, we show that unpredictability is associated with bistable dynamics preferably chaotic, and, furthermore, there is a tipping point associated with unpredictable dynamics.

Chimera states are spatiotemporal patterns in which distinct dynamics coexist, such as synchronous and asynchronous patterns. In this work, we study the effect of spike timing-dependent plasticity (STDP) on the emergence of chimera states. We consider a regular network of coupled adaptive exponential integrate-and-fire neurons, where all connections initially have the same strength value. The STDP alters the strength value as a function of the timing between the pre and postsynaptic action potentials over time. We verify that the range of parameters displaying chimera states is larger in the network with plasticity than in the absence of plasticity. Our simulations show that the chimera lifetime increases when the plasticity actuates in the neuronal network. We also observe an increase in neuronal spike frequency when the neurons are submitted to a constant positive current. In the parameter space, the changes in synaptic weights increase the appearance of chimera states.

Oscillatory activities in the brain, detected by electroencephalograms, have identified synchronization patterns. These synchronized activities in neurons are related to cognitive processes. Additionally, experimental research studies on neuronal rhythms have shown synchronous oscillations in brain disorders. Mathematical modeling of networks has been used to mimic these neuronal synchronizations. Actually, networks with scale-free properties were identified in some regions of the cortex. In this work, to investigate these brain synchronizations, we focus on neuronal synchronization in a network with coupled scale-free networks. The networks are connected according to a topological organization in the structural cortical regions of the human brain. The neuronal dynamic is given by the Rulkov model, which is a two-dimensional iterated map. The Rulkov neuron can generate quiescence, tonic spiking, and bursting. Depending on the parameters, we identify synchronous behavior among the neurons in the clustered networks. In this work, we aim to suppress the neuronal burst synchronization by the application of an external perturbation as a function of the mean-field of membrane potential. We found that the method we used to suppress synchronization presents better results when compared to the time-delayed feedback method when applied to the same model of the neuronal network.

Chaotic transport is a subject of paramount importance in a variety of problems in plasma physics, specially those related to anomalous transport and turbulence. On the other hand, a great deal of information on chaotic transport can be obtained from simple dynamical systems like two-dimensional area-preserving (symplectic) maps, where powerful mathematical results like KAM theory are available. In this work, we review recent works on transport barriers in area-preserving maps, focusing on systems which do not obey the so-called twist property. For such systems, usual KAM theory no longer holds everywhere and novel dynamical features show up as non-resistive reconnection, shearless curves, and shearless bifurcations. After presenting some general features using a standard nontwist mapping, we consider magnetic field line maps for magnetically confined plasmas in tokamaks.

Made available in DSpace on 2021-06-25T10:52:37Z (GMT). No. of bitstreams: 0 Previous issue date: 2021-02-01 The routes to chaos play an important role in predictions about the transitions from regular to irregular behavior in nonlinear dynamical systems, such as electrical oscillators, chemical reactions, biomedical rhythms, and nonlinear wave coupling. Of special interest are dissipative systems obtained by adding a dissipation term in a given Hamiltonian system. If the latter satisfies the so-called twist property, the corresponding dissipative version can be called a dissipative twist system.Transitions to chaos in these systems are well established; for instance, the Curry-Yorke route describes the transition from a quasiperiodic attractor on torus to chaos passing by a chaotic banded attractor. In this paper, we study the transitions from an attractor on torus to chaotic motion in dissipative nontwist systems. We choose the dissipative standard nontwist map, which is a non-conservative version of the standard nontwist map. In our simulations, we observe the same transition to chaos that happens in twist systems, known as a soft one, where the quasiperiodic attractor becomes wrinkled and then chaotic through the Curry-Yorke route. By the Lyapunov exponent, we study the nature of the orbits for a different set of parameters, and we observe that quasiperiodic motion and periodic and chaotic behavior are possible in the system. We observe that they can coexist in the phase space, implying in multistability. The different coexistence scenarios were studied by the basin entropy and by the boundary basin entropy. Department of Physics Federal University of Paraná Department of Mathematics and Statistics State University of Ponta Grossa Graduate in Science Program - Physics State University of Ponta Grossa Institute of Physics University of São Paulo Department of Statistics Applied Mathematics and Computer Science Institute of Geosciences and Exact Sciences Ͽ IGCE São Paulo State University (UNESP) Department of Statistics Applied Mathematics and Computer Science Institute of Geosciences and Exact Sciences Ͽ IGCE São Paulo State University (UNESP)

Much work has been done to investigate social jetlag, a misalignment between the biological clock and the social agenda caused by exposition to different light inputs, that causes several health issues. To investigate synchronization and attractors due to a sequence of light inputs, we introduce an extension of a model, previously used to describe jetlag caused by a single change in the light input. The synchronization to the light input is sensitive to the control parameters of the system and to the light input periods. Depending on the parameter set, the observed synchronization is with one or another successive light input. Most of the solutions have the period of a light input. However, for some parameters, we also observed higher period, chaotic solutions, and bistability., Comment: article 21 pages 8 figures, supplementary material 10 pages, 7 figures

Infectious diseases are caused by pathogenic microorganisms and can spread through different ways. Mathematical models and computational simulation have been used extensively to investigate the transmission and spread of infectious diseases. In other words, mathematical model simulation can be used to analyse the dynamics of infectious diseases, aiming to understand the effects and how to control the spread. In general, these models are based on compartments, where each compartment contains individuals with the same characteristics, such as susceptible, exposed, infected, and recovered. In this paper, we cast further light on some classical epidemic models, reporting possible outcomes from numerical simulation. Furthermore, we provide routines in a repository for simulations.

We study the advection of blood particles in the carotid bifurcation, a site that is prone to plaque development. Previously, it has been shown that chaotic advection can take place in blood flows with diseases. Here, we show that even in a healthy scenario, chaotic advection can take place. To understand how the particle dynamics is affected by the emergence and growth of a plaque, we study the carotid bifurcation in three cases: a healthy bifurcation, a bifurcation with a mild stenosis, and the another with a severe stenosis. The result is non-intuitive: there is less chaos for the mild stenosis case even when compared to the healthy, non-stenosed, bifurcation. This happens because the partial obstruction of the mild stenosis generates a symmetry in the flow that does not exist for the healthy condition. For the severe stenosis, there is more irregular motion and more particle trapping as expected.

Non-monotonic area-preserving maps violate the twist condition locally in phase space, giving rise to shearless invariant barriers surrounded by twin island chains in these regions of phase space. For the extended standard nontwist map, with two resonant perturbations with distinct wave numbers, we investigate the presence of such barriers and their associated island chains and compare our results with those that have been reported for the standard nontwist map with only one perturbation. Furthermore, we determine in the control parameter space the existence of the shearless barrier and the influence of the additional wave number on this condition. We show that only for odd second wave numbers are the twin island chains symmetrical. Moreover, for even wave numbers, the lack of symmetry between the chains of twin islands generates a ratchet effect that implies a directed transport in the phase space.

Chimera states are spatiotemporal patterns in which coherent and incoherent dynamics coexist simultaneously. These patterns were observed in both locally and nonlocally coupled oscillators. We study the existence of chimera states in networks of coupled Rössler oscillators. The Rössler oscillator can exhibit periodic or chaotic behavior depending on the control parameters. In this work, we show that the existence of coherent, incoherent, and chimera states depends not only on the coupling strength, but also on the initial state of the network. The initial states can belong to complex basins of attraction that are not homogeneously distributed. Due to this fact, we characterize the basins by means of the uncertainty exponent and basin stability. In our simulations, we find basin boundaries with smooth, fractal, and riddled structures.

The human cerebral cortex can be separated into cortical areas forming a clustered network structure. We build two different clustered networks, where one network is based on a healthy brain and the other according to a brain affected by a neurodegenerative process. Each cortical area has a subnetwork with small-world properties. We verify that both networks exhibit rich-club organisation and phase synchronisation. Due to the fact that neuronal synchronisation can be related to brain diseases, we consider the delayed feedback control as a method to suppress synchronous behaviours. In this work, it is presented that depending on the feedback parameters, intensity and time delay, phase synchronisation in both networks can be suppressed. Therefore, one of our main results is to show that delayed feedback control can be used to suppress undesired synchronous behaviours not only in the healthy brain, but also in the brain marked by neurodegenerative processes.

In certain circumstances, plasma response suppresses magnetic islands expected at perturbed resonant magnetic surfaces. We investigate the plasma response to the resonant magnetic perturbations in a large aspect ratio tokamak perturbed by external resonant helical windings, considering polar toroidal coordinates for which analytical toroidal equilibrium solutions and perturbing fields are available. We apply an empirical approach to mimic the plasma screening effects by introducing presumed plasma current sheets on the resonance surfaces to cancel the RMP effects. Numerical examples show the effect of plasma response reducing magnetic islands at the plasma edge and also regularizing field lines around the resonant surface. The distribution of connection lengths along the plasma cross section indicates that the plasma response increases the connection lengths since more toroidal turns are performed until a field line reaches the tokamak wall.

Evidences of internal particle transport barriers have been observed in plasma discharges with reversed plasma flow. To investigate the influence of the radial electric field profile on these barriers, we apply a drift wave map that describe the plasma particle transport and allows the integration of particle drift in the presence of a given electrostatic turbulence spectrum. With this procedure we show that transport barriers due to the shearless flow invariant lines are created inside the plasma. Moreover, by varying the radial electric field profile, we observe the formation and destruction of internal transport barriers constituted by shearless invariant lines, as well as its effects on the transport in the map's phase space. Applicability of our results are discussed for the Texas Helimak, a toroidal plasma device in which the radial electric field can be changed by application of bias potential.

Statistical properties for recurrent and non recurrent escaping particles in an oval billiard with holes in the boundary are investigated. We determine where to place the holes and where to launch particles in order to maximize or minimize the escape measurement. Initially, we introduce a fixed hole in the billiard boundary, injecting particles through the hole and analyzing the survival probability of the particles inside of the billiard. We show there are preferential regions to observe the escape of particles. Next, with two holes in the boundary, we obtain the escape basins of the particles and show the influence of the stickiness and the small chains of islands along the phase space in the escape of particles. Finally, we discuss the relation between the escape basins boundary, the uncertainty about the boundary points, the fractal dimension of them and the so called Wada property that appears when three holes are introduced in the boundary.

Periodic orbits are fundamental to nonlinear systems. We investigate periodic orbits for a dissipative mapping, derived from a prototype model of a non-linear driven oscillator with fast relaxation and a limit cycle. We show numerically the exponential growth of periodic orbits quantity and provide an analytical bound for such growth rate, by making use of the transition matrix associated with a given periodic orbit. Furthermore, we give numerical evidence to support that optimal orbits, those that maximize time averages, are often unstable periodic orbits with low period, by numerically comparing their performance under a family of sinusoidal functions.

Open hamiltonian systems have typically fractal structures underlying chaotic dynamics with a number of physical consequences on transport. We consider such fractal structures related to the formation of a chaotic magnetic field line region near the tokamak wall and the corresponding field line dynamics, described by a two-dimensional area-preserving map. We focus on the exit basins, which are sets of points which originate orbits escaping through some exit and are typically fractal, also exhibiting the so-called Wada property. We show qualitative as well as quantitative evidences of these properties.

Neuronal systems have been modelled by complex networks in different description levels. Recently, it has been verified that the networks can simultaneously exhibit one coherent and other incoherent domain, known as chimera states. In this work, we study the existence of chimera-like states in a network considering the connectivity matrix based on the cat cerebral cortex. The cerebral cortex of the cat can be separated in 65 cortical areas organised into the four cognitive regions: visual, auditory, somatosensory-motor and frontolimbic. We consider a network where the local dynamics is given by the Hindmarsh–Rose model. The Hindmarsh–Rose equations are a well known model of the neuronal activity that has been considered to simulate the membrane potential in neuron. Here, we analyse under which conditions chimera-like states are present, as well as the effects induced by intensity of coupling on them. We identify two different kinds of chimera-like states: spiking chimera-like state with desynchronised spikes, and bursting chimera-like state with desynchronised bursts. Moreover, we find that chimera-like states with desynchronised bursts are more robust to neuronal noise than with desynchronised spikes.

We would like to thank the partial support of this work by the Brazilian agencies FAPESP (processes: 2011/19296-1 and 2013/26598-0, CNPq and CAPES. MSB acknowledges EPSRC Ref. EP/I032606/1.

Stickiness is a well known phenomenon in which chaotic orbits expend an expressive amount of time in specific regions of the chaotic sea. This phenomenon becomes important when dealing with area-preserving open systems because, in this case, it leads to a temporary trapping of orbits in certain regions of phase space. In this work, we propose that the different scenarios of dynamical trapping can be explained by analyzing the crossings between invariant manifolds. In order to corroborate this assertion, we use an adaptive refinement procedure to approximately obtain the sets of homoclinic and heteroclinic intersections for the area-preserving H\'enon map, an archetype of open systems, for a generic parameter interval. We show that these sets have very different statistical properties when the system is highly influenced by dynamical trapping, whereas they present similar properties when stickiness is almost absent. We explain these different scenarios by taking into consideration various effects that occur simultaneously in the system, all of which are connected with the topology of the invariant manifolds., Comment: 10 pages, 8 figures

In Hamiltonian systems, depending on the control parameter, orbits can stay for very long times around islands, the so-called stickiness effect caused by a temporary trapping mechanism. Different methods have been used to identify sticky orbits, such as recurrence analysis, recurrence time statistics, and finite-time Lyapunov exponent. However, these methods require a large number of map iterations and to know the island positions in the phase space. Here, we show how to use the small divergence of bursts in the rotation number calculation as a tool to identify stickiness without knowing the island positions. This new procedure is applied to the standard map, a map that has been used to describe the dynamic behavior of several nonlinear systems. Moreover, our procedure uses a small number of map iterations and is proper to identify the presence of stickiness phenomenon for different values of the control parameter.

Made available in DSpace on 2020-12-12T00:56:55Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-10-01 Numerical experiments of the statistical evolution of an ensemble of noninteracting particles in a time-dependent billiard with inelastic collisions reveals the existence of three statistical regimes for the evolution of the speed ensemble, namely, diffusion plateau, normal growth/exponential decay, and stagnation. These regimes are linked numerically to the transition from Gauss-like to Boltzmann-like speed distributions. Furthermore, the different evolution regimes are obtained analytically through velocity-space diffusion analysis. From these calculations, the asymptotic root mean square of speed, initial plateau, and the growth/decay rates for an intermediate number of collisions are determined in terms of the system parameters. The analytical calculations match the numerical experiments and point to a dynamical mechanism for thermalization, where inelastic collisions and a high-dimensional phase space lead to a bounded diffusion in the velocity space toward a stationary distribution function with a kind of reservoir temperature determined by the boundary oscillation amplitude and the restitution coefficient. Instituto de Física Universidade de São Paulo Instituto de Astronomia Geofísica e Ciências Atmosféricas Universidade de São Paulo Departamento de Física UNESP Departamento de Física UNESP

We investigate theoretically the nonlinear dynamics and the emergence of chaos in suspended beam micro/nanoelectromechanical (MEMS/NEMS) resonators actuated by two-sided electrodes. Through the analysis of phase diagrams we have found that the system presents a rich and complex nonlinear behavior. Multistability is observed in a significant region of the relevant parameter space, involving periodic and chaotic attractors. Complex and varied routes to chaos were also found. Basins of attraction with strongly intermingled attractors provide further evidence of multistability. The basins are analyzed in greater detail. Their fractal dimensions and uncertainty exponent are calculated using the well known box counting and uncertainty methods. The results for the uncertainty exponent are compared with those obtained with yet another approach, based on the recently proposed basin entropy method. The comparison provides a test for the new approach, which we conclude that is a reliable alternative method of calculation. Very low uncertainty exponents have been obtained, indicating that some basins have extremely intermingled attractors, what may have significant influence in the experimental investigation and practical applications of the resonators. We also conclude that the observation of chaos in this system is favored by lower frequencies of excitation and comparatively small quality factors (larger dissipation).

An equation of state of a gas of electrons of dense matter at high pressure is proposed with basis on the Thomas-Fermi theory by taking into account a modification of an adiabatic relation. The formulation is applied to describe the behavior of the concentrations of alkali metals subjected to pressure excesses up to 100 , 000 kgf / cm 2 . The outcomes suggest a mechanism to explain the observed concentration discontinuity of Cesium. Also predicted are the values of the pressure excesses at which the concentrations of the remaining alkalies shall exhibit the same behavior as that of Cesium. The results may be of interest in the search for exoplanets, development of new materials, geologic metamorphism, among other related lines of investigation.

We investigate the synchronization properties of a neuronal network model inspired on the connection architecture of the human cerebral cortex. The neuronal model is composed of an assembly of networks, where each one of them is a scale-free network and the connections between them are taken from a human connectivity matrix proposed by Lo and collaborators [J. Neuroscience 30, 16876 (2010)]. The neuronal dynamics is governed by the Rulkov two-dimensional discrete-time map and the coupling between neurons and the different cortical regions occurs by means of chemical synapses. Individual neurons display bursting activity with characteristic phases and frequencies. Bursting synchronization is achieved for certain values of the chemical coupling strength in the network model and can be related to the presence of some pathological rhythms. The total or partial suppression of bursting synchronization has been pointed as a dynamical mechanism underlying deep brain stimulation techniques to mitigate such pathologies. In this work a synchronization suppression technique is employed through the application of an external signal based on the time-delayed mean field in certain areas of the neuronal network. Our results show that the suppression of synchronization depends on the values of the time delay and intensity of the applied signal.

Highlights • We investigate epidemic dynamics using a deterministic compartmental model and numerical simulations. • Examining the impact of easing restrictions on the infection rate for reopening the economy and society during COVID-19 pandemic. • A control strategy to suppress the spikes of infection cases for the period of easing containment measures., During an infectious disease outbreak, mathematical models and computational simulations are essential tools to characterize the epidemic dynamics and aid in design public health policies. Using these tools, we provide an overview of the possible scenarios for the COVID-19 pandemic in the phase of easing restrictions used to reopen the economy and society. To investigate the dynamics of this outbreak, we consider a deterministic compartmental model (SEIR model) with an additional parameter to simulate the restrictions. In general, as a consequence of easing restrictions, we obtain scenarios characterized by high spikes of infections indicating significant acceleration of the spreading disease. Finally, we show how such undesirable scenarios could be avoided by a control strategy of successive partial easing restrictions, namely, we tailor a successive sequence of the additional parameter to prevent spikes in phases of low rate of transmissibility.

We present a general formulation for magnetohydrostatic equilibria with external gravitational fields in symmetric systems with one ignorable coordinate, using non-orthogonal coordinate systems. We consider the cases of isothermal as well as adiabatic processes. Analytical exact solutions for the ideal magnetohydrodynamical equilibrium equation are presented for rectangular, cylindrical, and spherical coordinates.

We introduce two-dimensional symplectic maps to describe the Poincare maps of magnetic field lines in large aspect ratio tokamak equilibria with reversed non-monotonic plasma current density profiles. For these maps, we investigate the effect of the symmetry breaking due to the toroidal correction with a peculiar invariant, namely, a magnetic surface with a null rotation number, enclosing a vanishing current. We find that this rotationless invariant surface is surrounded by many small island chains. Furthermore, near such invariant, the symmetry breaking gives rise to two magnetic shearless invariants surrounded by twin island chains. We also find chaotic lines adjacent to all the observed islands created by the considered structurally unstable equilibria.

We investigate chaotic particle transport in magnetised plasmas with two electrostatic drift waves. Considering dissipation in the drift motion, we verify that the removed KAM surfaces originate periodic attractors with their corresponding basins of attraction. We show that the properties of the basins depend on the dissipation and the space-averaged escape time decays exponentially when the dissipation increases. We find positive finite time Lyapunov exponents in dissipative drift motion, consequently the trajectories exhibit transient chaotic transport. These features indicate how the transient plasma transport depends on the dissipation.

In this work, we apply the spatial recurrence quantification analysis (RQA) to identify chaotic burst phase synchronisation in networks. We consider one neural network with small-world topology and another one composed of small-world subnetworks. The neuron dynamics is described by the Rulkov map, which is a two-dimensional map that has been used to model chaotic bursting neurons. We show that with the use of spatial RQA, it is possible to identify groups of synchronised neurons and determine their size. For the single network, we obtain an analytical expression for the spatial recurrence rate using a Gaussian approximation. In clustered networks, the spatial RQA allows the identification of phase synchronisation among neurons within and between the subnetworks. Our results imply that RQA can serve as a useful tool for studying phase synchronisation even in networks of networks.

Made available in DSpace on 2018-12-11T16:53:25Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-03-01 The changeover from normal to super diffusion in time-dependent billiards is explained analytically. The unlimited energy growth for an ensemble of bouncing particles in time-dependent billiards is obtained by means of a two-dimensional mapping of the first and second moments of the speed distribution function. We prove that, for low initial speeds the average speed of the ensemble grows with exponent of the number of collisions with the boundary, therefore exhibiting normal diffusion. Eventually, this regime changes to a faster growth characterized by an exponent corresponding to super diffusion. For larger initial energies, the temporary symmetry in the diffusion of speeds explains an initial plateau of the average speed. Instituto de Física Universidade de Saõ Paulo Instituto de Física Universidade Federal Do Paraná Departamento de Física UNESP Departamento de Física UNESP

Chimera states, characterised by coexistence of coherence and incoherence in coupled dynamical systems, have been found in various physical systems, such as mechanical oscillator networks and Josephson-junction arrays. We used recurrence plots to provide graphical representations of recurrent patterns and identify chimera states. Moreover, we show that recurrence plots can be used as a diagnostic of chimera states and also to identify the chimera collapse.

O objetivo deste artigo é apresentar a concepção das leis de Kepler utilizando os aplicativos (livres) Stellarium e Geogebra para obter e analisar dados semelhantes aos que Kepler teve acesso. Embora o procedimento apresentado não seja exatamente igual ao de Kepler, ele permite, de forma didática, entender e aplicar a orientação seguida por ele para obter as leis sobre o movimento de planetas. Espera-se que o estudo quantitativo aqui desenvolvido esclareça o significado de algumas discussões qualitativas em diversas referências sobre este assunto e possa ser usado em aplicações didáticas.

Brain plasticity refers to brain’s ability to change neuronal connections, as a result of environmental stimuli, new experiences, or damage. In this work, we study the effects of the synaptic delay on both the coupling strengths and synchronization in a neuronal network with synaptic plasticity. We build a network of Hodgkin–Huxley neurons, where the plasticity is given by the Hebbian rules. We verify that without time delay the synapses become regulated by both the nature (excitatory or inhibitory) and the frequency of the presynaptic and postsynaptic neuron. A presynaptic excitatory (inhibitory) neuron with higher (lower) frequency enhances the synaptic strength if the postsynaptic excitatory (inhibitory) neuron has lower (higher) frequency. When the delay is increased the network presents a non-trivial topology. Regarding the synchronization, only for small values of the synaptic delay this phenomenon is observed.

Brain plasticity, also known as neuroplasticity, is a fundamental mechanism of neuronal adaptation in response to changes in the environment or due to brain injury. In this review, we show our results about the effects of synaptic plasticity on neuronal networks composed by Hodgkin-Huxley neurons. We show that the final topology of the evolved network depends crucially on the ratio between the strengths of the inhibitory and excitatory synapses. Excitation of the same order of inhibition revels an evolved network that presents the rich-club phenomenon, well known to exist in the brain. For initial networks with considerably larger inhibitory strengths, we observe the emergence of a complex evolved topology, where neurons sparsely connected to other neurons, also a typical topology of the brain. The presence of noise enhances the strength of both types of synapses, but if the initial network has synapses of both natures with similar strengths. Finally, we show how the synchronous behaviour of the evolved network will reflect its evolved topology.

Plasma turbulence at the edge of tokamaks is an issue of major importance in the study of the anomalous transport of particles and energy. Although the behavior of a turbulent plasma seems intractable, it turns out that many of its aspects can be described by low-dimensional non-integrable dynamical models. In this paper, we consider a number of dynamical effects occurring in tokamak plasma edge—in particular the role of internal transport barriers. Furthermore, we present experimental results on turbulent-driven transport for two machines—the Brazilian TCABR tokamak and University of Texas’ Helimak—that can be explained by those theoretical models.

In parameter space of nonlinear dynamical systems, windows of periodic states are aligned following the routes of period-adding configuring periodic window sequences. In state space of driven nonlinear oscillators, we determine the torsion associated with the periodic states and identify regions of uniform torsion in the window sequences. Moreover, we find that the measured torsion differs by a constant between successive windows in periodic window sequences. Finally, combining the torsion-adding phenomenon, reported in this work, and the known period-adding rule, we deduce a general rule to obtain the asymptotic winding number in the accumulation limit of such periodic window sequences.

This article was written to students of mathematics, physics and engineering. In general, the word chaos may refer to any state of confusion or disorder and it may also refer to mythology or philosophy. In science and mathematics it is understood as irregular behavior sensitive to initial conditions. In this article we analyze the deterministic chaos theory, a branch of mathematics and physics that deals with dynamical systems (nonlinear differential equations or mappings) with very peculiar properties. Fundamental concepts of the deterministic chaos theory are briefly analyzed and some illustrative examples of conservative and dissipative chaotic motions are introduced. Complementarily, we studied in details the chaotic motion of some dynamical systems described by differential equations and mappings. Relations between chaotic, stochastic and turbulent phenomena are also commented.

We have studied the effects of perturbations on the cat's cerebral cortex. According to the literature, this cortex structure can be described by a clustered network. This way, we construct a clustered network with the same number of areas as in the cat matrix, where each area is described as a sub-network with a small-world property. We focus on the suppression of neuronal phase synchronisation considering different kinds of perturbations. Among the various controlling interventions, we choose three methods: delayed feedback control, external time-periodic driving, and activation of selected neurons. We simulate these interventions to provide a procedure to suppress undesired and pathological abnormal rhythms that can be associated with many forms of synchronisation. In our simulations, we have verified that the efficiency of synchronisation suppression by delayed feedback control is higher than external time-periodic driving and activation of selected neurons of the cat's cerebral cortex with the same coupling strengths.

We analyze long-range time correlations and self-similar characteristics of the electrostatic turbulence at the plasma edge and scrape-off layer in the Tokamak Chauffage Alfven Bresillien (TCABR), with low and high Magnetohydrodynamics (MHD) activity. We find evidence of self-organized criticality (SOC), mainly in the region near the tokamak limiter. Comparative analyses of data before and during the MHD activity reveals that during the high MHD activity the Hurst parameter decreases. Finally, we present a cellular automaton whose parameters are adjusted to simulate the analyzed turbulence SOC change with the MHD activity variation.

In this work, we introduce an exact calculation method and an approximation technique for tracing the invariant manifolds of unstable periodic orbits of planar maps. The exact method relies on an adaptive refinement procedure that prevents redundant calculations occurring in other approaches, and the approximated method relies on a novel interpolation approach based on normal displacement functions. The resulting approximated manifold is precise when compared to the exact one, and its relative computational cost falls like the inverse of the manifold length. To present the tracing method, we obtain the invariant manifolds of the Chirikov-Taylor map, and as an application we illustrate the transition from homoclinic to heteroclinic chaos in the Duffing oscillator that leads from localized chaos to global chaotic motion.