Analysis of a cross-diffusion model for rival gangs interaction in a city

35 pages, 14 figuresWe study a two-species cross-diffusion model that is inspired by a system of convection-diffusion equations derived from an agent-based model on a two-dimensional discrete lattice. The latter model has been proposed to simulate gang territorial development through the use of graffiti markings. We find two energy functionals for the system that allow us to prove a weak-stability result and identify equilibrium solutions. We show that under the natural definition of weak solutions, obtained from the weak-stability result, the system does not allow segregated solutions. Moreover, we present a result on the long-term behavior of solutions in the case when the product of the mass of the densities are less than one. This result is complemented with numerical experiments

Phase Transitions in a Kinetic Flocking Model of Cucker--Smale Type

We consider a collective behavior model in which individuals try to imitate each others' velocity and have a preferred speed. We show that a phase change phenomenon takes place as diffusion decreases, bringing the system from a “disordered” to an “ordered” state. This effect is related to recently noticed phenomena for the diffusive Vicsek model. We also carry out numerical simulations of the system and give further details on the phase transition

Modeling and Simulations of the Spawning Migration of Pelagic Fish

We model the spawning migration of the Icelandic capelin stock using an interacting particle model with added environmental fields. Without artificial forcing terms or a homing instinct, we qualitatively reproduce several observed spawning migrations using available temperature data and approximated currents. The simulations include orders of magnitude more particles than many similar models, affecting the global behavior of the system. Without environmental fields, we analyze how various parameters scale with the number of particles. In particular we present scaling behavior between the size of the time step, radii of the sensory zones and the number of particles in the system. We then discuss incorporating environmental data into the model