Synchronization in an evolving network

In this work we study the dynamics of Kuramoto oscillators on a stochastically evolving network whose evolution is governed by the phases of the individual oscillators and degree distribution. Synchronization is achieved after a threshold connection density is reached. This cumulative effect of topology and dynamics has many real-world implications, where synchronization in a system emerges as a collective property of its components in a self-organizing manner. The synchronous state remains stable as long as the connection density remains above the threshold value, with additional links providing resilience against network fluctuations.Comment: 4 pages, 4 figure

Jamming in a lattice model of stochastically interacting agents with a field of view

We study the collective dynamics of a lattice model of stochastically interacting agents with a weighted field of vision. We assume that agents preferentially interact with neighbours, depending on their relative location, through velocity alignments and the additional constraint of exclusion. Unlike in previous models of flocking, here the stochasticity arises intrinsically from the interactions between agents, and its strength is dependent on the local density of agents. We find that this system yields a first-order jamming transition as a consequence of these interactions, even at a very low density. Furthermore, the critical jamming density is found to strongly depend on the nature of the field of view.Comment: 5 pages, 3 figures + 3 pages supplementary materia