9 research outputs found

    A nontwist field line mapping in a tokamak with ergodic magnetic limiter

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    For tokamaks with uniform magnetic shear, Martin and Taylor have proposed a symplectic map has been used to describe the magnetic field lines at the plasma edge perturbed by an ergodic magnetic limiter. We propose an analytical magnetic field line map, based on the Martin-Taylor map, for a tokamak with arbitrary safety factor profile. With the inclusion of a non-monotonic profile, we obtain a nontwist map which presents the characteristic properties of degenerate systems, as the twin islands scenario, the shearless curve and separatrix reconnection. We estimate the width of the islands and describe their changes of shape for large values of the limiter current. From our numerical simulations about the shearless curve, we show that its position and aspect depend on the control parameters

    Identification of single- and double-well coherence-incoherence patterns by the binary distance matrix

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    The study of chimera states or, more generally, coherence-incoherence patterns has led to the development of several tools for their identification and characterization. In this work, we extend the eigenvalue decomposition method to distinguish between single-well and double-well patterns. By applying our method, we are able to identify the following four types of dynamical patterns in a ring of nonlocally coupled Chua circuits and nonlocally coupled cubic maps: single-well cluster, single-well coherence-incoherence pattern, double-well cluster, and double-well coherence-incoherence. In a ring-star network of Chua circuits, we investigate the influence of adding a central node on the spatio-temporal patterns. Our results show that increasing the coupling with the central node favors the occurrence of single-well coherence-incoherence states. We observe that the boundaries of the attraction basins resemble fractal and riddled structure

    Fractional dynamics and recurrence analysis in cancer model

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    In this work, we analyze the effects of fractional derivatives in the chaotic dynamics of a cancer model. We begin by studying the dynamics of a standard model, {\it i.e.}, with integer derivatives. We study the dynamical behavior by means of the bifurcation diagram, Lyapunov exponents, and recurrence quantification analysis (RQA), such as the recurrence rate (RR), the determinism (DET), and the recurrence time entropy (RTE). We find a high correlation coefficient between the Lyapunov exponents and RTE. Our simulations suggest that the tumor growth parameter (ρ1\rho_1) is associated with a chaotic regime. Our results suggest a high correlation between the largest Lyapunov exponents and RTE. After understanding the dynamics of the model in the standard formulation, we extend our results by considering fractional operators. We fix the parameters in the chaotic regime and investigate the effects of the fractional order. We demonstrate how fractional dynamics can be properly characterized using RQA measures, which offer the advantage of not requiring knowledge of the fractional Jacobian matrix. We find that the chaotic motion is suppressed as α\alpha decreases, and the system becomes periodic for αâȘ…0.9966\alpha \lessapprox 0.9966. We observe limit cycles for α∈(0.9966,0.899)\alpha \in (0.9966,0.899) and fixed points for α<0.899\alpha<0.899. The fixed point is determined analytically for the considered parameters. Finally, we discover that these dynamics are separated by an exponential relationship between α\alpha and ρ1\rho_1. Also, the transition depends on a supper transient which obeys the same relationship

    Unpredictability in seasonal infectious diseases spread

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    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

    Effects of drug resistance in the tumour-immune system with chemotherapy treatment

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    Acknowledgement This study was possible by partial financial support from the following Brazilian government agencies: Fundaao Araucaria, National Council for Scientific and Technological Development, Coordination for the Improvement of Higher Education Personnel, and Sao Paulo Research Foundation (2015/07311-7, 2017/18977- 1, 2018/03211-6, 2020/04624-2)Peer reviewedPostprin
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