Collective traffic-like movement of ants on a trail: dynamical phases and phase transitions

Physics – Condensed Matter – Statistical Mechanics

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

8 pages, 6 figures

Scientific paper

10.1143/JPSJ.73.2979

The traffic-like collective movement of ants on a trail can be described by a stochastic cellular automaton model. We have earlier investigated its unusual flow-density relation by using various mean field approximations and computer simulations. In this paper, we study the model following an alternative approach based on the analogy with the zero range process, which is one of the few known exactly solvable stochastic dynamical models. We show that our theory can quantitatively account for the unusual non-monotonic dependence of the average speed of the ants on their density for finite lattices with periodic boundary conditions. Moreover, we argue that the model exhibits a continuous phase transition at the critial density only in a limiting case. Furthermore, we investigate the phase diagram of the model by replacing the periodic boundary conditions by open boundary conditions.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Collective traffic-like movement of ants on a trail: dynamical phases and phase transitions does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Collective traffic-like movement of ants on a trail: dynamical phases and phase transitions, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Collective traffic-like movement of ants on a trail: dynamical phases and phase transitions will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-353170

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.