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M. A. F. Sanjuán

Publications and source records attributed to M. A. F. Sanjuán.

7 recordsLinked to original sources

From Hyperbolic to Non-Hyperbolic Open Billiards: An Entropy and Scaling Law Approach

We investigate the escape dynamics in an open circular billiard under the influence of a uniform gravitational field. The system properties are investigated as a function of the particle total energy and the size of two symmetrically placed holes in the boundary. Using a suite of quantitative tools including escape basins, basin entropy ($S_b$), mean escape time ($\barτ$), and survival probability ($P(n)$), we characterize a system that transitions from a fully chaotic, hyperbolic regime at low energies to a non-hyperbolic, mixed phase space at higher energies. Our results demonstrate that this transition is marked by the emergence of Kolmogorov-Arnold-Moser (KAM) islands. We show that both the basin entropy and the mean escape time are sensitive to this transition, with the former peaking and the latter increasing sharply as the sticky KAM islands appear. The survival probability analysis confirms this dynamical picture, shifting from a pure exponential decay in the hyperbolic regime to a power-law-like decay with a saturation plateau in the mixed regime, which directly quantifies the measure of trapped orbits. In the high-energy limit, the system dynamics approaches an integrable case, leading to a corresponding decrease in complexity as measured by both $S_b$ and $\barτ$.

nlin.CD↗

Impact of Network Heterogeneity on Neuronal Synchronization

Synchronization dynamics is a phenomenon of great interest in many fields of science. One of the most important fields is neuron dynamics, as synchronization in certain regions of the brain is related to some of the most common mental illnesses. To study the impact of the network heterogeneity in the neuronal synchronization, we analyze a small-world network of non-identical Chialvo neurons that are electrically coupled. We introduce a mismatch in one of the model parameters to introduce the heterogeneity of the network. Our study examines the effects of this parameter mismatch, the noise intensity in the stochastic model, and the coupling strength between neurons on synchronization and firing frequency. We have identified critical values of noise intensity, parameter mismatch, and rewiring probability that facilitate effective synchronization within the network. Furthermore, we observe that the balance between excitatory and inhibitory connections plays a crucial role in achieving global synchronization. Our findings offer insights into the mechanisms driving synchronization dynamics in complex neuron networks.

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Basin entropy and the impact of the escape positioning in an open area-preserving map

The main properties of a dynamical system can be analyzed by examining the corresponding basins, either attraction basins in dissipative systems or escape basins in open Hamiltonian systems and area-preserving maps. In the latter case, the selection of the openings is crucial, as the way exits are chosen can directly influence the results. This study explores the impact of different opening choices on the escape basins by employing a model of particles transported along field lines in tokamaks with reversed shear. We quantitatively evaluate these phenomena using the concept of basin entropy across various system configurations. Our findings reveal that the positioning of the exits significantly affects the complexity and behavior of the escape basins, with remarkable abrupt changes in basin entropy linked to the choice of exits.

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Transient chaos under coordinate transformations in relativistic systems

We use the Hénon-Heiles system as a paradigmatic model for chaotic scattering to study the Lorentz factor effects on its transient chaotic dynamics. In particular, we focus on how time dilation occurs within the scattering region by measuring the time in a clock attached to the particle. We observe that the several events of time dilation that the particle undergoes exhibit sensitivity to initial conditions. However, the structure of the singularities appearing in the escape time function remains invariant under coordinate transformations. This occurs because the singularities are closely related to the chaotic saddle. We then demonstrate using a Cantor-like set approach that the fractal dimension of the escape time function is relativistic invariant. In order to verify this result, we compute by means of the uncertainty dimension algorithm the fractal dimensions of the escape time functions as measured with inertial and comoving with the particle frames. We conclude that, from a mathematical point of view, chaotic transient phenomena are equally predictable in any reference frame and that transient chaos is coordinate invariant.

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Effects of the spike timing-dependent plasticity on the synchronisation in a random Hodgkin-Huxley neuronal network

In this paper, we study the effects of spike timing-dependent plasticity on synchronisation in a network of Hodgkin-Huxley neurons. Neuron plasticity is a flexible property of a neuron and its network to change temporarily or permanently their biochemical, physiological, and morphological characteristics, in order to adapt to the environment. Regarding the plasticity, we consider Hebbian rules, specifically for spike timing-dependent plasticity (STDP), and with regard to network, we consider that the connections are randomly distributed. We analyse the synchronisation and desynchronisation according to an input level and probability of connections. Moreover, we verify that the transition for synchronisation depends on the neuronal network architecture, and the external perturbation level.

q-bio.NC↗

The interplay of university and industry through the FP5 network

To improve the quality of life in a modern society it is essential to reduce the distance between basic research and applications, whose crucial roles in shaping today's society prompt us to seek their understanding. Existing studies on this subject, however, have neglected the network character of the interaction between university and industry. Here we use state-of-the-art network theory methods to analyze this interplay in the so-called Framework Programme--an initiative which sets out the priorities for the European Union's research and technological development. In particular we study in the 5th Framework Programme (FP5) the role played by companies and scientific institutions and how they contribute to enhance the relationship between research and industry. Our approach provides quantitative evidence that while firms are size hierarchically organized, universities and research organizations keep the network from falling into pieces, paving the way for an effective knowledge transfer.

physics.soc-ph↗

Sparse repulsive coupling enhances synchronization in complex networks

Through the last years, different strategies to enhance synchronization in complex networks have been proposed. In this Letter, we show that the synchronization in a small-world network of attractively coupled non-identical neurons is strongly improved by adding a tiny fraction of phase-repulsive couplings. By a purely topological analysis that does not depend on the dynamical model, we link the emerging dynamical behavior to the structural properties of the sparsely coupled repulsive network.

cond-mat.dis-nn↗