English

Tracer Diffusion on a Crowded Random Manhattan Lattice

Disordered Systems and Neural Networks 2020-06-24 v3

Abstract

We study by extensive numerical simulations the dynamics of a hard-core tracer particle (TP) in presence of two competing types of disorder - frozen convection flows on a square random Manhattan lattice and a crowded dynamical environment formed by a lattice gas of mobile hard-core particles. The latter perform lattice random walks, constrained by a single-occupancy condition of each lattice site, and are either insensitive to random flows (model A) or choose the jump directions as dictated by the local directionality of bonds of the random Manhattan lattice (model B). We focus on the TP disorder-averaged mean-squared displacement, (which shows a super-diffusive behaviour t4/3\sim t^{4/3}, tt being time, in all the cases studied here), on higher moments of the TP displacement, and on the probability distribution of the TP position XX along the xx-axis. Our analysis evidences that in absence of the lattice gas particles the latter has a Gaussian central part exp(u2)\sim \exp(- u^2), where u=X/t2/3u = X/t^{2/3}, and exhibits slower-than-Gaussian tails exp(u4/3)\sim \exp(-|u|^{4/3}) for sufficiently large tt and uu. Numerical data convincingly demonstrate that in presence of a crowded environment the central Gaussian part and non-Gaussian tails of the distribution persist for both models.

Keywords

Cite

@article{arxiv.1912.03169,
  title  = {Tracer Diffusion on a Crowded Random Manhattan Lattice},
  author = {Carlos Mejía-Monasterio and Sergei Nechaev and Gleb Oshanin and Oleg Vasilyev},
  journal= {arXiv preprint arXiv:1912.03169},
  year   = {2020}
}

Comments

24 pages, 6 figures

R2 v1 2026-06-23T12:38:09.411Z