Current fluctuations in boundary driven diffusive systems in different dimensions: a numerical study
arXiv:1502.07559 · doi:10.1088/1367-2630/17/5/055023
Abstract
We use kinetic Monte Carlo simulations to investigate current fluctuations in boundary driven generalized exclusion processes, in different dimensions. Simulation results are in full agreement with predictions based on the additivity principle and the macroscopic fluctuation theory. The current statistics are independent of the shape of the contacts with the reservoirs, provided they are macroscopic in size. In general, the current distribution depends on the spatial dimension. For the special cases of the symmetric simple exclusion process and the zero-range process, the current statistics are the same for all spatial dimensions.
21 pages, 11 figures, published version
References in corpus (15)
- The large deviation approach to statistical mechanics
- Non equilibrium steady states: fluctuations and large deviations of the density and of the current
- A numerical approach to large deviations in continuous-time
- Steady state statistics of driven diffusions
- Cumulants and large deviations of the current through non-equilibrium steady states
- Symmetries in Fluctuations Far from Equilibrium
- Large deviations of heat flow in harmonic chains
- DMRG-study of current and activity fluctuations near non-equilibrium phase transitions
- Current Fluctuations and Statistics During a Large Deviation Event in an Exactly-Solvable Transport Model
- Factorised Steady States in Mass Transport Models on an Arbitrary Graph
- Large Fluctuations of the Macroscopic Current in Diffusive Systems: A Confirmation of the Additivity Principle
- Transient fluctuation theorems for the currents and initial equilibrium ensembles
- Extreme Fluctuations of Current in the Symmetric Simple Exclusion Process: a Non-Stationary Setting
- Diffusion of interacting particles in discrete geometries: equilibrium and dynamical properties
- Adsorption and desorption in confined geometries: a discrete hopping model