English

Aggregation-fragmentation-diffusion model for trail dynamics

Statistical Mechanics 2017-07-24 v1

Abstract

We investigate statistical properties of trails formed by a random process incorporating aggregation, fragmentation, and diffusion. In this stochastic process, which takes place in one spatial dimension, two neighboring trails may combine to form a larger one and also, one trail may split into two. In addition, trails move diffusively. The model is defined by two parameters which quantify the fragmentation rate and the fragment size. In the long-time limit, the system reaches a steady state, and our focus is the limiting distribution of trail weights. We find that the density of trail weight has power-law tail P(w)wγP(w) \sim w^{-\gamma} for small weight ww. We obtain the exponent γ\gamma analytically, and find that it varies continuously with the two model parameters. The exponent γ\gamma can be positive or negative, so that in one range of parameters small-weight tails are abundant, and in the complementary range, they are rare.

Keywords

Cite

@article{arxiv.1705.05400,
  title  = {Aggregation-fragmentation-diffusion model for trail dynamics},
  author = {Kyle Kawagoe and Greg Huber and Marc Pradas and Michael Wilkinson and Alain Pumir and Eli Ben-Naim},
  journal= {arXiv preprint arXiv:1705.05400},
  year   = {2017}
}

Comments

8 pages, 8 figures

R2 v1 2026-06-22T19:47:45.165Z