Bunching of extreme events on complex network

Extreme events such as earthquakes, floods, and power blackouts often display burst phenomena where multiple extreme events occur in quick succession or in bunches. We show that the network structure plays an important role in bunching of extreme events. We use a model of independent random walkers on a complex network. We find that independent walkers on a network with two clusters connected sparsely show oscillatory behavior between the two clusters. A small cluster sparsely connected with the rest of the network shows correlations and bunching among extreme events. The bunching and correlations emerge naturally in our system though the walkers are independent. Such correlations and bunching are not observed in the large cluster. Thus, these correlations are driven by the network structure. We use several characterization techniques, namely, the recurrence time distribution, autocorrelation function, bursty trains, burstiness parameter, and memory coefficient to quantify the bunching and correlations of extreme events.