Spatiotemporal chaos on a regular ring network of excitable Gray-Scott dynamical elements collapses to a stable asymptotic state. We find that the addition of dynamical noise clearly influences the spatiotemporal pattern and the transient lifetime of spatiotemporal chaos. Spatially uniform noise significantly decreases the average lifetime of spatiotemporal chaos due to an enlargement of regions of local collapse. For spatially inhomogeneous noise the collapse is maximally delayed at an intermediate noise level, but drastically advanced for larger noise levels.
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http://dx.doi.org/10.1103/PhysRevE.75.066209 | DOI Listing |
Chaos
January 2025
School of Mathematical & Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom.
Time-evolving graphs arise frequently when modeling complex dynamical systems such as social networks, traffic flow, and biological processes. Developing techniques to identify and analyze communities in these time-varying graph structures is an important challenge. In this work, we generalize existing spectral clustering algorithms from static to dynamic graphs using canonical correlation analysis to capture the temporal evolution of clusters.
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January 2025
Department of Physics, Tohoku University, Sendai 980-8578, Japan.
An Ott-Antonsen reduced M-population of Kuramoto-Sakaguchi oscillators is investigated, focusing on the influence of the phase-lag parameter α on the collective dynamics. For oscillator populations coupled on a ring, we obtained a wide variety of spatiotemporal patterns, including coherent states, traveling waves, partially synchronized states, modulated states, and incoherent states. Back-and-forth transitions between these states are found, which suggest metastability.
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December 2024
Centre for Mathematical Biology and Ecology, Department of Mathematics, Jadavpur University, Kolkata 700032, India.
This study expands traditional reaction-diffusion models by incorporating hyperbolic dynamics to explore the effects of inertial delays on pattern formation. The kinetic system considers a harvested predator-prey model where predator and prey populations gather in herds. Diffusion and inertial effects are subsequently introduced.
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October 2024
Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany; Institute for the Dynamics of Complex Systems, Georg-August-Universität Göttingen, Göttingen, Germany; and German Center for Cardiovascular Research (DZHK e.V., Partner Site Niedersachsen, Göttingen, Germany.
Life-threatening cardiac arrhythmias such as ventricular fibrillation are often based on chaotic spiral or scroll wave dynamics which can be self-terminating. In this work, we investigate the influence of conduction heterogeneities on the duration of such chaotic transients in generic models of excitable cardiac media. We observe that low and medium densities of heterogeneities extend the average transient lifetime, while at high densities very long transients, potentially persistent chaos, and periodic attractors occur.
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November 2024
Center for Nonlinear Dynamics in Medicine, Southeast University, Nanjing 210096, China.
Exploring spatiotemporal patterns of high-dimensional electroencephalography (EEG) time series generated from complex brain system is crucial for deciphering aging and cognitive functioning. Analyzing high-dimensional EEG series poses challenges, particularly when employing distance-based methods for spatiotemporal dynamics. Therefore, we proposed an innovative methodology for multi-channel EEG data, termed as Spatiotemporal Information-based Similarity (STIBS) analysis.
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