Ruby Varshney , Anjuman Ara Khatun , Haider Hasan Jafri
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引用次数: 0
Abstract
We study the transition to phase synchronization in an ensemble of Stuart–Landau oscillators interacting on a star network. We observe that by introducing frequency-weighted coupling and timescale variations in the dynamics of nodes, the system exhibits a first-order explosive transition to phase synchrony. Further, we extend this study to understand the nature of synchronization in the case of two coupled star networks. If the coupled star networks are identical, we observe that with increasing inter-star coupling strength, the hysteresis width initially increases, reaches a maximum value, then decreases before saturating. If the interacting star networks are non-identical, we observe that the transition to the coherent state is preceded by the occurrence of intermittent in-phase and anti-phase synchrony for small inter-star coupling. However, for large values of coupling strengths, we observe that the intermittent state disappears and the hysteresis width changes as in coupled identical star networks. We characterize these transitions by plotting the Lyapunov exponents for the system and the master stability function.
期刊介绍:
Computational Science is a rapidly growing multi- and interdisciplinary field that uses advanced computing and data analysis to understand and solve complex problems. It has reached a level of predictive capability that now firmly complements the traditional pillars of experimentation and theory.
The recent advances in experimental techniques such as detectors, on-line sensor networks and high-resolution imaging techniques, have opened up new windows into physical and biological processes at many levels of detail. The resulting data explosion allows for detailed data driven modeling and simulation.
This new discipline in science combines computational thinking, modern computational methods, devices and collateral technologies to address problems far beyond the scope of traditional numerical methods.
Computational science typically unifies three distinct elements:
• Modeling, Algorithms and Simulations (e.g. numerical and non-numerical, discrete and continuous);
• Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems;
• Computer and information science that develops and optimizes the advanced system hardware, software, networking, and data management components (e.g. problem solving environments).