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Interactions amongst agents frequently exist only at particular moments in time, depending on their closeness in space and movement parameters. Here we propose a minimal model of moving agents where the network of contacts changes over time due to their motion. In particular, agents interact based on their proximity in a two-dimensional space, but only if they belong to the same fixed interaction zones. Our research reveals the emergence of global synchronization if all the interaction zones are attractive. However, if some of the interaction zones are repulsive, they deflect synchrony and lead to short-lasting but recurrent deviations that constitute extreme events in the network. We use two paradigmatic oscillators for the description of the agent dynamics to demonstrate our findings numerically, and we also provide an analytical formulation to describe the emergence of complete synchrony and the thresholds that distinguish extreme events from other intermittent states based on the peak-over-threshold approach. [ABSTRACT FROM AUTHOR]

Synchronization in time-varying (i.e., dynamic) network has been explored using different types of couplings during the last two decades. In this paper, we consider a dynamic network where the spatial position of each node decides the number of nodes with which it interacts. We analytically derive the density-dependent threshold of coupling strength for synchrony using linear stability analysis and numerically verify the obtained results. We use two paradigmatic chaotic systems, namely the Rössler and Lorenz models to affirm our claims. [ABSTRACT FROM AUTHOR]