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Sudharsan S

Publications and source records attributed to Sudharsan S.

2 recordsLinked to original sources

Intermittent cluster synchronization in a unidirectional ring of bursting neurons

We report a new mechanism through which extreme events with a dragon king-like distribution emerge in a network of unidirectional ring of Hindmarsh-Rose bursting neurons interacting through chemical synapses. We establish and substantiate the fact that depending on the choice of initial conditions, the neurons are divided into different clusters. These clusters transit from a phase-locked state (anti-phase) to phase synchronized regime with increasing value of the coupling strength. Before attaining phase synchronization, there exists some regions of the coupling strength where these clusters are phase synchronized intermittently. During such intermittent phase synchronization, extreme events originate in the mean-field of the membrane potential. This mechanism, which we name as intermittent cluster synchronization, is proposed as the new precursor for the generation of emergent extreme events in this system. These results are also true for diffusive coupling (gap junctions). The distribution of the local maxima of the collective observable shows a long tailed non-Gaussian while the interevent interval follows the Weibull distribution. The goodness of fit are corroborated using probability-probability plot and quantile-quantile plot. This intermittent phase synchronization becomes rarer and rarer with the increase in the number of clusters of initial conditions.

nlin.CD

Symmetrical emergence of extreme events at multiple regions in a damped and driven velocity-dependent mechanical system

In this work, we report the emergence of extreme events in a damped and driven velocity-dependent mechanical system. We observe that the extreme events emerge at multiple points. We further notice that the extreme events occur symmetrically in both positive and negative values at all the points of emergence. We statistically confirm the emergence of extreme events by plotting the probability distribution function of peaks and interevent intervals. We also determine the mechanism behind the emergence of extreme events at all the points and classify these points into two categories depending on the region at which the extreme events emerge. Finally, we plot the two parameter diagram in order to have a complete overview of the system.

nlin.CD