Tracer diffusion on a crowded random Manhattan lattice

Mejía-Monasterio, Carlos, Nechaev, Sergei, Oshanin, Gleb and Vasilyev, Oleg (2020). Tracer diffusion on a crowded random Manhattan lattice. "New Journal of Physics", v. 22 ; pp.. ISSN 1367-2630.


Title: Tracer diffusion on a crowded random Manhattan lattice
  • Mejía-Monasterio, Carlos
  • Nechaev, Sergei
  • Oshanin, Gleb
  • Vasilyev, Oleg
Item Type: Article
Título de Revista/Publicación: New Journal of Physics
Date: March 2020
ISSN: 1367-2630
Volume: 22
Freetext Keywords: random Manhattan lattice; tracer diffusion; hard-core lattice gas; simple exclusion process; quenched versus dynamical disorder
Faculty: E.T.S. de Ingeniería Agronómica, Alimentaria y de Biosistemas (UPM)
Department: Ingeniería Agroforestal
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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, t being time, in all the cases studied here), on higher moments of the TP displacement, and on the probability distribution of the TP position X along the x-axis. Our analysis evidences that in absence of the lattice gas particles the latter has a Gaussian central part ∼exp(−u2), where u=X/t2/3, and exhibits slower-than-Gaussian tails ∼exp(−|u|4/3) for sufficiently large t and u. 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.

Funding Projects

Government of Spain
Transporte activo y búsquedas probabilistas en ambientes complejos

More information

Item ID: 64199
DC Identifier:
OAI Identifier:
DOI: 10.1088/1367-2630/ab7bf1
Official URL:
Deposited by: Memoria Investigacion
Deposited on: 19 Oct 2020 07:21
Last Modified: 19 Oct 2020 07:21
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