Fractal Concepts in Surface Growth

A host of spatially extended systems, both in physics and in other disciplines, are well described at a coarsegrained scale by a Langevin equation with multiplicative-noise. Such systems may exhibit nonequilibrium phase transitions, which can be classified into universality classes. Here we study in detail one such class that can be mapped into a Kardar-Parisi-Zhang (KPZ) interface equation with a positive (negative) non-linearity in the presence of a bounding lower (upper) wall. The wall limits the possible values taken by the height variable, introducing a lower (upper) cut-off, and induces a phase transition between a pinned (active) and a depinned (absorbing) phase. This transition is studied here using mean field and field theoretical arguments, as well as from a numerical point of view. Its main properties and critical features, as well as some challenging theoretical difficulties, are reported. The differences with other multiplicative noise and bounded-KPZ universality classes are stressed, and the effects caused by the introduction of "attractive" walls, relevant in some physical contexts, are also analyzed.

Section: V2 Modelsupporting

confidence: 89%

Critical behavior of a bounded Kardar-Parisi-Zhang equation

Muñoz¹,

Santos²,

Achahbar

2003

“…There is also a great interest in modeling interface growth [6,7], traffic flow [8], temperature dependent catalytic reactions [9], etc. Nonequilibrium magnetic systems, with a well defined hamiltonian, have been also studied in the context of nonequilibrium processes [10,11] as well.…”

Section: Introductionmentioning

confidence: 99%

Catalysis with competitive reactions: static and dynamical critical behavior

Costa

Figueiredo²

2003

We studied in this work a competitive reaction model between monomers on a catalyst. The catalyst is represented by hypercubic lattices in d = 1, 2 and 3 dimensions. The model is described by the following reactions: A + A → A2 and A + B → AB, where A and B are two monomers that arrive at the surface with probabilities y A and y B , respectively. The model is studied in the adsorption controlled limit where the reaction rate is infinitely larger than the adsorption rate. We employ site and pair mean-field approximations as well as static and dynamical Monte Carlo simulations. We show that, for all d, the model exhibits a continuous phase transition between an active steady state and a B-absorbing state, when the parameter y A is varied through a critical value. Monte Carlo simulations and finite-size scaling analysis near the critical point are used to determine the static critical exponents β, ν ⊥ and the dynamical critical exponents ν || , δ, η and z. The results found for this competitive reaction model are in accordance with the conjecture of Grassberger, which states that any system undergoing a continuous phase transition from an active steady state to a single absorbing state, exhibits the same critical behavior of the directed percolation universality class. I IntroductionIn the course of the last decade the statistical mechanics community has made great progress in the study of nonequilibrium phenomena. Until now, we do not have a complete theory accounting for the nonequilibrium systems. The fundamental concept of a Gibbsian distribution of states in equilibrium has no counterpart in the nonequilibrium situation. This happens because many of these systems do not present even an hamiltonian function and, if it is possible to define an hamiltonian, the detailed balance would be violated.Examples of recent problems on nonequilibrium processes include markets [1, 2], rain precipitation [3], sandpiles [4] and conserved contact process [5]. There is also a great interest in modeling interface growth [6,7], traffic flow [8], temperature dependent catalytic reactions [9], etc. Nonequilibrium magnetic systems, with a well defined hamiltonian, have been also studied in the context of nonequilibrium processes [10,11] as well.For the equilibrium systems we can induce phase transitions by changing some external parameters. Usually, the temperature is the selected control parameter to study phase transitions between equilibrium states. In the case of continuous phase transitions, at the critical point, long range correlations are established inside the system and a set of critical exponents can be defined to describe the critical behavior of some thermodynamic properties. The renormalization group theory [12] is a well known theory that allows the calculation of these critical exponents.We can also consider external constraints for the nonequilibrium systems that can drive the dynamical behavior of the system. The nature of the external parameter depends on the nature of the system. For instance, in an epidemic mode...

“…As an example, we consider the random deposition (RD) model [1]. Particles are deposited randomly at a constant rate on a d-dimensional discrete substrate (L d lattice sites).…”

Section: Definitionsmentioning

confidence: 99%

“…Self-affine interfaces generated by non equilibrium surface growth have been intensively studied in the 1990's [1,2]. One of the reasons of interest is to distinguish universality classes to which these kinetic roughening models can belong.…”

Section: Introductionmentioning

confidence: 99%

Universality classes of chaotic cellular automata

Mattos

Moreira

2004

Cellular automata (CA) are discrete, spatially-homogeneous, locally-interacting dynamical systems of very simple construction, but which exhibit a rich intrinsic behavior. Even starting from disordered initial configurations, CA can evolve into ordered states with complex structures crystallized in space-time patterns. In this paper we concentrate on deterministic one-dimensional CA defined by rules that lead to chaotic patterns. In order to find universality classes for these rules we associate a growth process with the CA dynamics and study the temporal behavior of the growth exponent, skewness and kurtosis of the height distribution of the interface. We obtain four universality classes characterized by different values of the growth exponent. These are related to the random deposition and directed percolation classes.