Non-equilibrium relaxation and critical aging for driven Ising lattice gases
arXiv:1112.1605 · doi:10.1103/PhysRevLett.108.110602
Abstract
We employ Monte Carlo simulations to study the non-equilibrium relaxation of driven Ising lattice gases in two dimensions. Whereas the temporal scaling of the density auto-correlation function in the non-equilibrium steady state does not allow a precise measurement of the critical exponents, these can be accurately determined from the aging scaling of the two-time auto-correlations and the order parameter evolution following a quench to the critical point. We obtain excellent agreement with renormalization group predictions based on the standard Langevin representation of driven Ising lattice gases.
5 pages, 4 figures included; to appear in Phys. Rev. Lett. (2012)
References in corpus (4)
Cited by in corpus (16)
- Dynamic phase transition in the three-dimensional kinetic Ising model in an oscillating field
- Phase Transitions and Scaling in Systems Far From Equilibrium
- On the microscopic origin and macroscopic implications of lane formation in mixtures of oppositely-driven particles
- Non-equilibrium relaxation in a stochastic lattice Lotka-Volterra model
- Driving Driven Lattice Gases to Identify Their Universality Classes
- Logarithmic correlators or responses in non-relativistic analogues of conformal invariance
- Short-time Behaviour and Criticality of Driven Lattice Gases
- Critical initial-slip scaling for the noisy complex Ginzburg-Landau equation
- On the universal Gaussian behavior of Driven Lattice Gases at short-times
- Transverse Temperature Interfaces in the Katz-Lebowitz-Spohn Driven Lattice Gas
- Critical Scaling and Aging near the Flux Line Depinning Transition
- Universal Quench Dynamics of an Open Quantum System
- Aging phenomena in the two-dimensional complex Ginzburg-Landau equation
- Damage Spreading in a Driven Lattice Gas Model
- Parallel Temperature Interfaces in the Katz-Lebowitz-Spohn Driven Lattice Gas
- Agent-based Monte Carlo simulations for reaction-diffusion models, population dynamics, and epidemic spreading